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A researcher measures the sleep of 376 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 288 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 121 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 257 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 244 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 126 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 291 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 133 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 136 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 266 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 168 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 57 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 89 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 193 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 84 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 154 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 338 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 111 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 95 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 231 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 105 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 75 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 68 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 318 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 292 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 98 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 303 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 129 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 325 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 314 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 175 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 438 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 242 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 319 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 144 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 285 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 300 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 328 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 362 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 150 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 483 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 224 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 149 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 310 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 177 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 267 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 151 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 123 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 254 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
A researcher measures the sleep of 219 randomly chosen teenagers and finds a mean of 7.1 hours. What is 7.1?
1. A statistic: it describes the sample
2. A parameter: it describes all teenagers
3. The population
To learn how much US college students spend on books, a team surveys 671 students at 20 colleges. What is the population?
1. All US college students
2. The 671 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 351 students at 20 colleges. What is the population?
1. All US college students
2. The 351 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 876 students at 20 colleges. What is the population?
1. All US college students
2. The 876 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 464 students at 20 colleges. What is the population?
1. All US college students
2. The 464 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 319 students at 20 colleges. What is the population?
1. All US college students
2. The 319 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 417 students at 20 colleges. What is the population?
1. All US college students
2. The 417 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 858 students at 20 colleges. What is the population?
1. All US college students
2. The 858 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 637 students at 20 colleges. What is the population?
1. All US college students
2. The 637 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 178 students at 20 colleges. What is the population?
1. All US college students
2. The 178 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 262 students at 20 colleges. What is the population?
1. All US college students
2. The 262 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 217 students at 20 colleges. What is the population?
1. All US college students
2. The 217 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 333 students at 20 colleges. What is the population?
1. All US college students
2. The 333 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 230 students at 20 colleges. What is the population?
1. All US college students
2. The 230 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 536 students at 20 colleges. What is the population?
1. All US college students
2. The 536 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 208 students at 20 colleges. What is the population?
1. All US college students
2. The 208 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 639 students at 20 colleges. What is the population?
1. All US college students
2. The 639 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 539 students at 20 colleges. What is the population?
1. All US college students
2. The 539 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 622 students at 20 colleges. What is the population?
1. All US college students
2. The 622 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 580 students at 20 colleges. What is the population?
1. All US college students
2. The 580 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 588 students at 20 colleges. What is the population?
1. All US college students
2. The 588 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 209 students at 20 colleges. What is the population?
1. All US college students
2. The 209 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 461 students at 20 colleges. What is the population?
1. All US college students
2. The 461 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 334 students at 20 colleges. What is the population?
1. All US college students
2. The 334 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 859 students at 20 colleges. What is the population?
1. All US college students
2. The 859 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 282 students at 20 colleges. What is the population?
1. All US college students
2. The 282 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 658 students at 20 colleges. What is the population?
1. All US college students
2. The 658 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 696 students at 20 colleges. What is the population?
1. All US college students
2. The 696 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 556 students at 20 colleges. What is the population?
1. All US college students
2. The 556 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 762 students at 20 colleges. What is the population?
1. All US college students
2. The 762 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 832 students at 20 colleges. What is the population?
1. All US college students
2. The 832 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 355 students at 20 colleges. What is the population?
1. All US college students
2. The 355 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 712 students at 20 colleges. What is the population?
1. All US college students
2. The 712 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 427 students at 20 colleges. What is the population?
1. All US college students
2. The 427 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 833 students at 20 colleges. What is the population?
1. All US college students
2. The 833 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 462 students at 20 colleges. What is the population?
1. All US college students
2. The 462 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 677 students at 20 colleges. What is the population?
1. All US college students
2. The 677 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 104 students at 20 colleges. What is the population?
1. All US college students
2. The 104 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 774 students at 20 colleges. What is the population?
1. All US college students
2. The 774 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 569 students at 20 colleges. What is the population?
1. All US college students
2. The 569 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 519 students at 20 colleges. What is the population?
1. All US college students
2. The 519 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 280 students at 20 colleges. What is the population?
1. All US college students
2. The 280 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 635 students at 20 colleges. What is the population?
1. All US college students
2. The 635 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 493 students at 20 colleges. What is the population?
1. All US college students
2. The 493 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 227 students at 20 colleges. What is the population?
1. All US college students
2. The 227 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 808 students at 20 colleges. What is the population?
1. All US college students
2. The 808 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 188 students at 20 colleges. What is the population?
1. All US college students
2. The 188 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 877 students at 20 colleges. What is the population?
1. All US college students
2. The 877 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 789 students at 20 colleges. What is the population?
1. All US college students
2. The 789 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 669 students at 20 colleges. What is the population?
1. All US college students
2. The 669 students surveyed
3. The 20 colleges
To learn how much US college students spend on books, a team surveys 510 students at 20 colleges. What is the population?
1. All US college students
2. The 510 students surveyed
3. The 20 colleges
Census records show that 52% of all households in a town own a car. What is 52%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 55% of all households in a town own a car. What is 55%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 60% of all households in a town own a car. What is 60%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 40% of all households in a town own a car. What is 40%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 57% of all households in a town own a car. What is 57%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 42% of all households in a town own a car. What is 42%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 49% of all households in a town own a car. What is 49%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 51% of all households in a town own a car. What is 51%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 58% of all households in a town own a car. What is 58%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 50% of all households in a town own a car. What is 50%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 45% of all households in a town own a car. What is 45%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 53% of all households in a town own a car. What is 53%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 56% of all households in a town own a car. What is 56%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 59% of all households in a town own a car. What is 59%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 48% of all households in a town own a car. What is 48%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 47% of all households in a town own a car. What is 47%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 43% of all households in a town own a car. What is 43%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 46% of all households in a town own a car. What is 46%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 54% of all households in a town own a car. What is 54%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 41% of all households in a town own a car. What is 41%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
Census records show that 44% of all households in a town own a car. What is 44%?
1. A parameter: it describes the whole population
2. A statistic
3. A sample proportion
A school has 600 juniors and 300 seniors. A stratified sample of 90 students is taken in proportion to grade. How many juniors are in the sample?
A systematic sample of 30 customers is taken from a list of 480: a random start, then every $k$ th name. What is $k$ ?
A district has 60 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 88 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 76 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 63 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 83 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 80 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 82 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 44 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 45 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 79 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 68 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 40 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 50 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 87 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 84 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 52 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 77 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 65 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 56 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 70 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 71 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 48 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 54 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 66 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 62 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 61 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 86 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 55 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 73 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 57 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 49 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 81 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 47 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 69 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 58 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 53 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 51 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 42 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 78 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 59 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 90 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 46 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 72 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 75 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 41 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 89 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 64 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 43 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 67 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A district has 74 classrooms. Five are chosen at random and every student in them is surveyed. Which sampling method is this?
1. Cluster sampling
2. Stratified sampling
3. A simple random sample of students
A news website asks readers to vote online; 4824 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4824 responses are representative
A news website asks readers to vote online; 1714 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1714 responses are representative
A news website asks readers to vote online; 3716 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 3716 responses are representative
A news website asks readers to vote online; 1560 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1560 responses are representative
A news website asks readers to vote online; 1035 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1035 responses are representative
A news website asks readers to vote online; 1225 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1225 responses are representative
A news website asks readers to vote online; 866 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 866 responses are representative
A news website asks readers to vote online; 1442 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1442 responses are representative
A news website asks readers to vote online; 3042 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 3042 responses are representative
A news website asks readers to vote online; 2939 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 2939 responses are representative
A news website asks readers to vote online; 3780 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 3780 responses are representative
A news website asks readers to vote online; 3381 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 3381 responses are representative
A news website asks readers to vote online; 4312 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4312 responses are representative
A news website asks readers to vote online; 4089 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4089 responses are representative
A news website asks readers to vote online; 2087 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 2087 responses are representative
A news website asks readers to vote online; 4745 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4745 responses are representative
A news website asks readers to vote online; 4130 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4130 responses are representative
A news website asks readers to vote online; 1359 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1359 responses are representative
A news website asks readers to vote online; 2941 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 2941 responses are representative
A news website asks readers to vote online; 4407 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4407 responses are representative
A news website asks readers to vote online; 4025 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4025 responses are representative
A news website asks readers to vote online; 4086 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4086 responses are representative
A news website asks readers to vote online; 2631 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 2631 responses are representative
A news website asks readers to vote online; 598 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 598 responses are representative
A news website asks readers to vote online; 602 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 602 responses are representative
A news website asks readers to vote online; 4358 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4358 responses are representative
A news website asks readers to vote online; 3213 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 3213 responses are representative
A news website asks readers to vote online; 3873 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 3873 responses are representative
A news website asks readers to vote online; 1872 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1872 responses are representative
A news website asks readers to vote online; 1732 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1732 responses are representative
A news website asks readers to vote online; 4507 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4507 responses are representative
A news website asks readers to vote online; 3855 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 3855 responses are representative
A news website asks readers to vote online; 3591 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 3591 responses are representative
A news website asks readers to vote online; 1002 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1002 responses are representative
A news website asks readers to vote online; 3188 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 3188 responses are representative
A news website asks readers to vote online; 1545 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1545 responses are representative
A news website asks readers to vote online; 1734 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1734 responses are representative
A news website asks readers to vote online; 1949 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1949 responses are representative
A news website asks readers to vote online; 1077 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1077 responses are representative
A news website asks readers to vote online; 1979 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1979 responses are representative
A news website asks readers to vote online; 4847 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4847 responses are representative
A news website asks readers to vote online; 1616 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1616 responses are representative
A news website asks readers to vote online; 2473 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 2473 responses are representative
A news website asks readers to vote online; 1938 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1938 responses are representative
A news website asks readers to vote online; 4351 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4351 responses are representative
A news website asks readers to vote online; 1755 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1755 responses are representative
A news website asks readers to vote online; 4385 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4385 responses are representative
A news website asks readers to vote online; 2748 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 2748 responses are representative
A news website asks readers to vote online; 1328 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 1328 responses are representative
A news website asks readers to vote online; 4228 vote and 80% favor a new law. What is the main problem?
1. Voluntary response bias: people with strong opinions choose to respond
2. The sample is too small
3. None: 4228 responses are representative
A survey of 115 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 715 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 619 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 410 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 361 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 189 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 159 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 369 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 443 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 510 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 196 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 749 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 763 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 563 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 707 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 675 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 145 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 326 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 211 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 471 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 415 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 775 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 798 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 873 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 858 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 440 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 138 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 108 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 897 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 585 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 608 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 418 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 104 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 484 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 496 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 302 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 291 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 193 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 631 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 634 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 487 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 803 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 556 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 868 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 889 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 411 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 458 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 668 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 151 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A survey of 422 adults is done by calling landline numbers. What kind of bias is most likely?
1. Undercoverage: people without landlines cannot be chosen
2. Response bias from the wording
3. None, if the numbers are chosen at random
A biased survey of 238 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 402 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 520 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 555 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 666 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 583 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 355 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 891 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 718 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 517 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 819 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 307 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 446 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 789 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 392 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 126 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 706 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 653 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 352 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 403 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 300 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 462 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 708 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 253 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 862 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 205 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 609 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 846 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 867 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 288 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 351 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 496 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 223 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 692 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 705 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 473 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 740 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 600 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 357 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 188 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 700 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 289 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 756 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 640 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 396 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 835 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 864 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 833 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 721 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
A biased survey of 136 people is repeated with 10 times as many people, chosen the same way. What happens to the bias?
1. It stays: a larger sample reduces random variability, not bias
2. It disappears
3. It becomes 10 times smaller
Researchers randomly assign 66 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 166 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 46 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 133 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 173 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 144 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 40 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 45 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 195 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 189 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 141 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 196 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 112 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 78 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 96 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 169 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 145 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 152 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 129 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 65 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 97 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 70 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 109 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 111 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 51 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 49 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 197 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 188 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 161 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 179 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 155 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 125 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 74 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 177 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 59 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 147 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 124 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 41 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 48 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 93 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 192 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 110 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 200 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 178 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 153 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 84 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 180 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 151 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 194 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Researchers randomly assign 163 volunteers to drink coffee or water, then test their reaction times. What kind of study is it?
1. An experiment: the researchers assign the treatment
2. An observational study
3. A sample survey
Children with bigger shoes read better (16% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (13% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (30% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (37% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (36% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (35% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (20% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (23% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (15% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (25% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (27% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (39% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (10% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (18% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (22% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (29% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (17% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (38% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (34% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (19% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (12% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (26% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (33% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (31% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (14% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (24% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (11% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (28% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (21% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (32% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
Children with bigger shoes read better (40% higher scores). What is the most likely explanation?
1. A confounding variable: age affects both shoe size and reading
2. Bigger feet improve reading
3. It must be pure chance
An observational study of 3416 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 5700 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 8655 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 1601 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 5074 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 7764 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 2314 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 3314 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 2139 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 6746 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 4943 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 863 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 1943 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 3273 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 7388 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 8847 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 8745 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 745 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 2788 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 4529 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 5749 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 1756 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 5236 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 3831 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 3387 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 632 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 576 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 4932 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 8595 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 3079 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 4804 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 4762 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 2487 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 8033 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 614 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 798 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 8965 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 3192 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 2599 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 1147 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 1724 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 1811 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 4824 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 7222 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 1744 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 7929 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 3510 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 7028 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 2504 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
An observational study of 5206 adults finds that those who eat breakfast weigh less. Does this show that eating breakfast causes lower weight?
1. No: other differences between the groups could explain it
2. Yes, because the sample is large
3. Yes, if the association is strong
Why are 196 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 185 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 189 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 46 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 188 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 47 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 65 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 101 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 66 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 102 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 111 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 85 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 54 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 84 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 75 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 122 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 129 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 61 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 57 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 92 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 132 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 55 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 178 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 96 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 41 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 184 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 182 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 118 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 179 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 154 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 169 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 43 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 97 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 143 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 183 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 76 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 48 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 79 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 151 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 60 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 147 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 78 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 83 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 139 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 155 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 69 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 103 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 115 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 187 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
Why are 198 subjects assigned to the treatments at random?
1. To balance other variables between the groups, so differences can be blamed on the treatment
2. So the results apply to the whole population
3. To give every subject the same chance of being in the study
A test of two diets on 115 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 45 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 100 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 94 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 68 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 88 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 72 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 128 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 179 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 90 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 141 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 122 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 97 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 142 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 78 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 139 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 84 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 193 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 149 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 163 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 170 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 79 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 73 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 106 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 105 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 157 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 75 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 155 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 191 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 200 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 110 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 70 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 159 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 188 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 156 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 129 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 53 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 87 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 185 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 41 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 40 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 150 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 116 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 121 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 176 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 147 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 140 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 168 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 93 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
A test of two diets on 160 adults first splits them into men and women, then randomizes diets within each group. What is this design?
1. A randomized block design, blocking by sex
2. A stratified random sample
3. A completely randomized design
An experiment tests 2 fertilizer types at 5 watering levels, with every combination used. How many treatments are there?
A random sample of 493 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 493 people sampled
A random sample of 530 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 530 people sampled
A random sample of 712 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 712 people sampled
A random sample of 837 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 837 people sampled
A random sample of 303 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 303 people sampled
A random sample of 459 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 459 people sampled
A random sample of 235 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 235 people sampled
A random sample of 824 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 824 people sampled
A random sample of 799 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 799 people sampled
A random sample of 826 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 826 people sampled
A random sample of 821 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 821 people sampled
A random sample of 768 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 768 people sampled
A random sample of 780 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 780 people sampled
A random sample of 515 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 515 people sampled
A random sample of 389 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 389 people sampled
A random sample of 522 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 522 people sampled
A random sample of 544 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 544 people sampled
A random sample of 212 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 212 people sampled
A random sample of 791 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 791 people sampled
A random sample of 775 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 775 people sampled
A random sample of 734 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 734 people sampled
A random sample of 268 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 268 people sampled
A random sample of 567 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 567 people sampled
A random sample of 314 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 314 people sampled
A random sample of 773 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 773 people sampled
A random sample of 625 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 625 people sampled
A random sample of 656 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 656 people sampled
A random sample of 298 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 298 people sampled
A random sample of 829 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 829 people sampled
A random sample of 345 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 345 people sampled
A random sample of 679 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 679 people sampled
A random sample of 230 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 230 people sampled
A random sample of 372 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 372 people sampled
A random sample of 749 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 749 people sampled
A random sample of 288 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 288 people sampled
A random sample of 483 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 483 people sampled
A random sample of 583 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 583 people sampled
A random sample of 714 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 714 people sampled
A random sample of 370 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 370 people sampled
A random sample of 241 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 241 people sampled
A random sample of 717 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 717 people sampled
A random sample of 640 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 640 people sampled
A random sample of 716 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 716 people sampled
A random sample of 558 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 558 people sampled
A random sample of 272 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 272 people sampled
A random sample of 858 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 858 people sampled
A random sample of 561 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 561 people sampled
A random sample of 375 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 375 people sampled
A random sample of 454 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 454 people sampled
A random sample of 707 adults in a city shows that those who walk to work report less stress. No treatment was assigned. What can be concluded?
1. The association can be generalized to adults in the city, but not cause and effect
2. Walking causes less stress for adults in the city
3. Nothing beyond the 707 people sampled
147 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
142 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
62 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
181 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
173 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
109 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
158 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
70 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
55 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
40 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
194 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
119 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
51 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
144 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
116 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
159 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
126 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
153 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
146 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
170 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
83 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
161 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
85 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
200 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
135 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
189 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
112 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
90 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
68 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
150 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
195 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
190 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
128 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
64 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
171 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
167 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
73 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
152 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
57 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
125 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
48 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
43 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
80 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
44 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
42 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
81 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
49 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
86 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
179 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
97 volunteers are randomly assigned to a new or old teaching method; the new method scores higher. What can be concluded?
1. The method caused the difference for these volunteers; generalizing beyond them is risky
2. The new method works better for all students
3. Nothing, because there was no random sample
In a drug trial with 64 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 116 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 155 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 66 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 104 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 41 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 48 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 97 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 149 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 156 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 123 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 101 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 138 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 108 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 189 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 192 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 73 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 163 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 90 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 62 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 161 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 179 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 196 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 44 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 100 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 50 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 70 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 112 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 106 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 59 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 75 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 126 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 120 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 51 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 87 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 140 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 71 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 65 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 43 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 165 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 153 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 94 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 89 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 92 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 197 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 49 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 173 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 115 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 195 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking
In a drug trial with 200 patients, neither the patients nor the doctors who assess them know who receives the drug. What is this called?
1. A double-blind experiment
2. A placebo
3. Blocking

Answers

A statistic: it describes the sample
All US college students
A parameter: it describes the whole population
$60$
$16$
Cluster sampling
Voluntary response bias: people with strong opinions choose to respond
Undercoverage: people without landlines cannot be chosen
It stays: a larger sample reduces random variability, not bias
An experiment: the researchers assign the treatment
A confounding variable: age affects both shoe size and reading
No: other differences between the groups could explain it
To balance other variables between the groups, so differences can be blamed on the treatment
A randomized block design, blocking by sex
$10$
The association can be generalized to adults in the city, but not cause and effect
The method caused the difference for these volunteers; generalizing beyond them is risky
A double-blind experiment