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A 95% confidence interval for a proportion is (39/100, 49/100). Find the margin of error.
A confidence interval for a mean is (41, 55). Find the point estimate.
A 95% interval from a sample of 591 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 890 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 583 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 819 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 508 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 266 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 427 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 482 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 108 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 642 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 670 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 745 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 320 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 141 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 172 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 294 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 681 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 157 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 369 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 220 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 726 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 276 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 156 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 414 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 398 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 236 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 399 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 311 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 898 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 247 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 595 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 719 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 411 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 684 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 589 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 503 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 758 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 848 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 349 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 459 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 393 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 844 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 662 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 205 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 545 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 520 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 534 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 143 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 739 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
A 95% interval from a sample of 693 is too wide. Which change makes it narrower?
1. A larger sample size
2. A higher confidence level, such as 99%
3. Nothing: the width is fixed by the population
In a random sample of 400, p̂ = 5/10. Using z* = 1.96, find the margin of error of a 95% interval for p.
In a random sample of 100, p̂ = 3/10. Using z* = 2, find the upper end of the approximate 95% interval for p.
A 95% confidence interval for the proportion of voters who support a plan is (0.48, 0.52). Which interpretation is right?
1. We are 95% confident that the interval from 0.48 to 0.52 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.48 and 0.52
A 95% confidence interval for the proportion of voters who support a plan is (0.31, 0.53). Which interpretation is right?
1. We are 95% confident that the interval from 0.31 to 0.53 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.31 and 0.53
A 95% confidence interval for the proportion of voters who support a plan is (0.44, 0.55). Which interpretation is right?
1. We are 95% confident that the interval from 0.44 to 0.55 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.44 and 0.55
A 95% confidence interval for the proportion of voters who support a plan is (0.41, 0.57). Which interpretation is right?
1. We are 95% confident that the interval from 0.41 to 0.57 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.41 and 0.57
A 95% confidence interval for the proportion of voters who support a plan is (0.50, 0.54). Which interpretation is right?
1. We are 95% confident that the interval from 0.50 to 0.54 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.50 and 0.54
A 95% confidence interval for the proportion of voters who support a plan is (0.31, 0.54). Which interpretation is right?
1. We are 95% confident that the interval from 0.31 to 0.54 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.31 and 0.54
A 95% confidence interval for the proportion of voters who support a plan is (0.40, 0.54). Which interpretation is right?
1. We are 95% confident that the interval from 0.40 to 0.54 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.40 and 0.54
A 95% confidence interval for the proportion of voters who support a plan is (0.43, 0.56). Which interpretation is right?
1. We are 95% confident that the interval from 0.43 to 0.56 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.43 and 0.56
A 95% confidence interval for the proportion of voters who support a plan is (0.33, 0.53). Which interpretation is right?
1. We are 95% confident that the interval from 0.33 to 0.53 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.33 and 0.53
A 95% confidence interval for the proportion of voters who support a plan is (0.35, 0.60). Which interpretation is right?
1. We are 95% confident that the interval from 0.35 to 0.60 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.35 and 0.60
A 95% confidence interval for the proportion of voters who support a plan is (0.37, 0.54). Which interpretation is right?
1. We are 95% confident that the interval from 0.37 to 0.54 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.37 and 0.54
A 95% confidence interval for the proportion of voters who support a plan is (0.50, 0.55). Which interpretation is right?
1. We are 95% confident that the interval from 0.50 to 0.55 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.50 and 0.55
A 95% confidence interval for the proportion of voters who support a plan is (0.41, 0.60). Which interpretation is right?
1. We are 95% confident that the interval from 0.41 to 0.60 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.41 and 0.60
A 95% confidence interval for the proportion of voters who support a plan is (0.44, 0.57). Which interpretation is right?
1. We are 95% confident that the interval from 0.44 to 0.57 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.44 and 0.57
A 95% confidence interval for the proportion of voters who support a plan is (0.50, 0.51). Which interpretation is right?
1. We are 95% confident that the interval from 0.50 to 0.51 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.50 and 0.51
A 95% confidence interval for the proportion of voters who support a plan is (0.31, 0.56). Which interpretation is right?
1. We are 95% confident that the interval from 0.31 to 0.56 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.31 and 0.56
A 95% confidence interval for the proportion of voters who support a plan is (0.38, 0.51). Which interpretation is right?
1. We are 95% confident that the interval from 0.38 to 0.51 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.38 and 0.51
A 95% confidence interval for the proportion of voters who support a plan is (0.48, 0.51). Which interpretation is right?
1. We are 95% confident that the interval from 0.48 to 0.51 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.48 and 0.51
A 95% confidence interval for the proportion of voters who support a plan is (0.46, 0.51). Which interpretation is right?
1. We are 95% confident that the interval from 0.46 to 0.51 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.46 and 0.51
A 95% confidence interval for the proportion of voters who support a plan is (0.50, 0.57). Which interpretation is right?
1. We are 95% confident that the interval from 0.50 to 0.57 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.50 and 0.57
A 95% confidence interval for the proportion of voters who support a plan is (0.47, 0.60). Which interpretation is right?
1. We are 95% confident that the interval from 0.47 to 0.60 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.47 and 0.60
A 95% confidence interval for the proportion of voters who support a plan is (0.33, 0.56). Which interpretation is right?
1. We are 95% confident that the interval from 0.33 to 0.56 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.33 and 0.56
A 95% confidence interval for the proportion of voters who support a plan is (0.33, 0.55). Which interpretation is right?
1. We are 95% confident that the interval from 0.33 to 0.55 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.33 and 0.55
A 95% confidence interval for the proportion of voters who support a plan is (0.43, 0.59). Which interpretation is right?
1. We are 95% confident that the interval from 0.43 to 0.59 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.43 and 0.59
A 95% confidence interval for the proportion of voters who support a plan is (0.35, 0.57). Which interpretation is right?
1. We are 95% confident that the interval from 0.35 to 0.57 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.35 and 0.57
A 95% confidence interval for the proportion of voters who support a plan is (0.40, 0.59). Which interpretation is right?
1. We are 95% confident that the interval from 0.40 to 0.59 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.40 and 0.59
A 95% confidence interval for the proportion of voters who support a plan is (0.49, 0.55). Which interpretation is right?
1. We are 95% confident that the interval from 0.49 to 0.55 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.49 and 0.55
A 95% confidence interval for the proportion of voters who support a plan is (0.36, 0.52). Which interpretation is right?
1. We are 95% confident that the interval from 0.36 to 0.52 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.36 and 0.52
A 95% confidence interval for the proportion of voters who support a plan is (0.46, 0.55). Which interpretation is right?
1. We are 95% confident that the interval from 0.46 to 0.55 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.46 and 0.55
A 95% confidence interval for the proportion of voters who support a plan is (0.43, 0.51). Which interpretation is right?
1. We are 95% confident that the interval from 0.43 to 0.51 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.43 and 0.51
A 95% confidence interval for the proportion of voters who support a plan is (0.42, 0.51). Which interpretation is right?
1. We are 95% confident that the interval from 0.42 to 0.51 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.42 and 0.51
A 95% confidence interval for the proportion of voters who support a plan is (0.49, 0.60). Which interpretation is right?
1. We are 95% confident that the interval from 0.49 to 0.60 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.49 and 0.60
A 95% confidence interval for the proportion of voters who support a plan is (0.32, 0.58). Which interpretation is right?
1. We are 95% confident that the interval from 0.32 to 0.58 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.32 and 0.58
A 95% confidence interval for the proportion of voters who support a plan is (0.30, 0.53). Which interpretation is right?
1. We are 95% confident that the interval from 0.30 to 0.53 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.30 and 0.53
A 95% confidence interval for the proportion of voters who support a plan is (0.46, 0.59). Which interpretation is right?
1. We are 95% confident that the interval from 0.46 to 0.59 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.46 and 0.59
A 95% confidence interval for the proportion of voters who support a plan is (0.44, 0.58). Which interpretation is right?
1. We are 95% confident that the interval from 0.44 to 0.58 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.44 and 0.58
A 95% confidence interval for the proportion of voters who support a plan is (0.47, 0.51). Which interpretation is right?
1. We are 95% confident that the interval from 0.47 to 0.51 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.47 and 0.51
A 95% confidence interval for the proportion of voters who support a plan is (0.44, 0.56). Which interpretation is right?
1. We are 95% confident that the interval from 0.44 to 0.56 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.44 and 0.56
A 95% confidence interval for the proportion of voters who support a plan is (0.39, 0.54). Which interpretation is right?
1. We are 95% confident that the interval from 0.39 to 0.54 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.39 and 0.54
A 95% confidence interval for the proportion of voters who support a plan is (0.34, 0.53). Which interpretation is right?
1. We are 95% confident that the interval from 0.34 to 0.53 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.34 and 0.53
A 95% confidence interval for the proportion of voters who support a plan is (0.49, 0.56). Which interpretation is right?
1. We are 95% confident that the interval from 0.49 to 0.56 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.49 and 0.56
A 95% confidence interval for the proportion of voters who support a plan is (0.30, 0.52). Which interpretation is right?
1. We are 95% confident that the interval from 0.30 to 0.52 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.30 and 0.52
A 95% confidence interval for the proportion of voters who support a plan is (0.43, 0.55). Which interpretation is right?
1. We are 95% confident that the interval from 0.43 to 0.55 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.43 and 0.55
A 95% confidence interval for the proportion of voters who support a plan is (0.32, 0.55). Which interpretation is right?
1. We are 95% confident that the interval from 0.32 to 0.55 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.32 and 0.55
A 95% confidence interval for the proportion of voters who support a plan is (0.50, 0.60). Which interpretation is right?
1. We are 95% confident that the interval from 0.50 to 0.60 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.50 and 0.60
A 95% confidence interval for the proportion of voters who support a plan is (0.31, 0.55). Which interpretation is right?
1. We are 95% confident that the interval from 0.31 to 0.55 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.31 and 0.55
A 95% confidence interval for the proportion of voters who support a plan is (0.39, 0.55). Which interpretation is right?
1. We are 95% confident that the interval from 0.39 to 0.55 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.39 and 0.55
A 95% confidence interval for the proportion of voters who support a plan is (0.44, 0.52). Which interpretation is right?
1. We are 95% confident that the interval from 0.44 to 0.52 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.44 and 0.52
A 95% confidence interval for the proportion of voters who support a plan is (0.48, 0.59). Which interpretation is right?
1. We are 95% confident that the interval from 0.48 to 0.59 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.48 and 0.59
A 95% confidence interval for the proportion of voters who support a plan is (0.49, 0.51). Which interpretation is right?
1. We are 95% confident that the interval from 0.49 to 0.51 captures the true proportion of supporters
2. 95% of the sample supports the plan
3. There is a 95% probability that p is between 0.49 and 0.51
From the same sample of 458, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 100, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 672, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 355, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 705, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 174, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 544, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 255, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 403, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 125, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 418, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 755, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 647, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 524, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 444, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 157, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 369, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 177, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 120, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 668, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 612, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 870, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 883, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 536, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 633, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 275, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 506, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 110, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 610, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 236, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 381, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 529, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 366, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 655, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 604, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 408, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 422, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 285, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 164, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 454, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 622, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 265, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 383, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 357, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 339, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 836, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 578, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 209, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 614, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
From the same sample of 811, a 99% and a 90% interval are computed. Which is wider?
1. The 99% interval
2. The 90% interval
3. They have the same width
What does the confidence level 90% mean?
1. In repeated random sampling, about 90% of the intervals built this way capture the parameter
2. This interval contains the parameter with probability 90%
3. 90% of the data fall in the interval
What does the confidence level 97% mean?
1. In repeated random sampling, about 97% of the intervals built this way capture the parameter
2. This interval contains the parameter with probability 97%
3. 97% of the data fall in the interval
What does the confidence level 98% mean?
1. In repeated random sampling, about 98% of the intervals built this way capture the parameter
2. This interval contains the parameter with probability 98%
3. 98% of the data fall in the interval
What does the confidence level 91% mean?
1. In repeated random sampling, about 91% of the intervals built this way capture the parameter
2. This interval contains the parameter with probability 91%
3. 91% of the data fall in the interval
What does the confidence level 93% mean?
1. In repeated random sampling, about 93% of the intervals built this way capture the parameter
2. This interval contains the parameter with probability 93%
3. 93% of the data fall in the interval
What does the confidence level 92% mean?
1. In repeated random sampling, about 92% of the intervals built this way capture the parameter
2. This interval contains the parameter with probability 92%
3. 92% of the data fall in the interval
What does the confidence level 96% mean?
1. In repeated random sampling, about 96% of the intervals built this way capture the parameter
2. This interval contains the parameter with probability 96%
3. 96% of the data fall in the interval
What does the confidence level 99% mean?
1. In repeated random sampling, about 99% of the intervals built this way capture the parameter
2. This interval contains the parameter with probability 99%
3. 99% of the data fall in the interval
What does the confidence level 94% mean?
1. In repeated random sampling, about 94% of the intervals built this way capture the parameter
2. This interval contains the parameter with probability 94%
3. 94% of the data fall in the interval
What does the confidence level 95% mean?
1. In repeated random sampling, about 95% of the intervals built this way capture the parameter
2. This interval contains the parameter with probability 95%
3. 95% of the data fall in the interval
A 95% interval (z* = 1.96) has margin of error 0.07. From the same data, find the margin of error of a 99% interval (z* = 2.576).
Using p = 0.5 and z* = 1.96, find the value of n (before rounding up) needed for a margin of error of 0.04.
A survey of 264 people gives a margin of error you want to halve. About how many people are needed?
1. 1056
2. 528
3. About half as many
A survey of 308 people gives a margin of error you want to halve. About how many people are needed?
1. 1232
2. 616
3. About half as many
A survey of 489 people gives a margin of error you want to halve. About how many people are needed?
1. 1956
2. 978
3. About half as many
A survey of 354 people gives a margin of error you want to halve. About how many people are needed?
1. 1416
2. 708
3. About half as many
A survey of 472 people gives a margin of error you want to halve. About how many people are needed?
1. 1888
2. 944
3. About half as many
A survey of 225 people gives a margin of error you want to halve. About how many people are needed?
1. 900
2. 450
3. About half as many
A survey of 166 people gives a margin of error you want to halve. About how many people are needed?
1. 664
2. 332
3. About half as many
A survey of 411 people gives a margin of error you want to halve. About how many people are needed?
1. 1644
2. 822
3. About half as many
A survey of 376 people gives a margin of error you want to halve. About how many people are needed?
1. 1504
2. 752
3. About half as many
A survey of 435 people gives a margin of error you want to halve. About how many people are needed?
1. 1740
2. 870
3. About half as many
A survey of 297 people gives a margin of error you want to halve. About how many people are needed?
1. 1188
2. 594
3. About half as many
A survey of 191 people gives a margin of error you want to halve. About how many people are needed?
1. 764
2. 382
3. About half as many
A survey of 119 people gives a margin of error you want to halve. About how many people are needed?
1. 476
2. 238
3. About half as many
A survey of 148 people gives a margin of error you want to halve. About how many people are needed?
1. 592
2. 296
3. About half as many
A survey of 477 people gives a margin of error you want to halve. About how many people are needed?
1. 1908
2. 954
3. About half as many
A survey of 210 people gives a margin of error you want to halve. About how many people are needed?
1. 840
2. 420
3. About half as many
A survey of 312 people gives a margin of error you want to halve. About how many people are needed?
1. 1248
2. 624
3. About half as many
A survey of 356 people gives a margin of error you want to halve. About how many people are needed?
1. 1424
2. 712
3. About half as many
A survey of 111 people gives a margin of error you want to halve. About how many people are needed?
1. 444
2. 222
3. About half as many
A survey of 369 people gives a margin of error you want to halve. About how many people are needed?
1. 1476
2. 738
3. About half as many
A survey of 240 people gives a margin of error you want to halve. About how many people are needed?
1. 960
2. 480
3. About half as many
A survey of 313 people gives a margin of error you want to halve. About how many people are needed?
1. 1252
2. 626
3. About half as many
A survey of 211 people gives a margin of error you want to halve. About how many people are needed?
1. 844
2. 422
3. About half as many
A survey of 238 people gives a margin of error you want to halve. About how many people are needed?
1. 952
2. 476
3. About half as many
A survey of 416 people gives a margin of error you want to halve. About how many people are needed?
1. 1664
2. 832
3. About half as many
A survey of 415 people gives a margin of error you want to halve. About how many people are needed?
1. 1660
2. 830
3. About half as many
A survey of 352 people gives a margin of error you want to halve. About how many people are needed?
1. 1408
2. 704
3. About half as many
A survey of 327 people gives a margin of error you want to halve. About how many people are needed?
1. 1308
2. 654
3. About half as many
A survey of 483 people gives a margin of error you want to halve. About how many people are needed?
1. 1932
2. 966
3. About half as many
A survey of 370 people gives a margin of error you want to halve. About how many people are needed?
1. 1480
2. 740
3. About half as many
A survey of 255 people gives a margin of error you want to halve. About how many people are needed?
1. 1020
2. 510
3. About half as many
A survey of 441 people gives a margin of error you want to halve. About how many people are needed?
1. 1764
2. 882
3. About half as many
A survey of 168 people gives a margin of error you want to halve. About how many people are needed?
1. 672
2. 336
3. About half as many
A survey of 455 people gives a margin of error you want to halve. About how many people are needed?
1. 1820
2. 910
3. About half as many
A survey of 244 people gives a margin of error you want to halve. About how many people are needed?
1. 976
2. 488
3. About half as many
A survey of 189 people gives a margin of error you want to halve. About how many people are needed?
1. 756
2. 378
3. About half as many
A survey of 345 people gives a margin of error you want to halve. About how many people are needed?
1. 1380
2. 690
3. About half as many
A survey of 409 people gives a margin of error you want to halve. About how many people are needed?
1. 1636
2. 818
3. About half as many
A survey of 233 people gives a margin of error you want to halve. About how many people are needed?
1. 932
2. 466
3. About half as many
A survey of 440 people gives a margin of error you want to halve. About how many people are needed?
1. 1760
2. 880
3. About half as many
A survey of 445 people gives a margin of error you want to halve. About how many people are needed?
1. 1780
2. 890
3. About half as many
A survey of 309 people gives a margin of error you want to halve. About how many people are needed?
1. 1236
2. 618
3. About half as many
A survey of 278 people gives a margin of error you want to halve. About how many people are needed?
1. 1112
2. 556
3. About half as many
A survey of 100 people gives a margin of error you want to halve. About how many people are needed?
1. 400
2. 200
3. About half as many
A survey of 216 people gives a margin of error you want to halve. About how many people are needed?
1. 864
2. 432
3. About half as many
A survey of 202 people gives a margin of error you want to halve. About how many people are needed?
1. 808
2. 404
3. About half as many
A survey of 279 people gives a margin of error you want to halve. About how many people are needed?
1. 1116
2. 558
3. About half as many
A survey of 208 people gives a margin of error you want to halve. About how many people are needed?
1. 832
2. 416
3. About half as many
A survey of 320 people gives a margin of error you want to halve. About how many people are needed?
1. 1280
2. 640
3. About half as many
A survey of 432 people gives a margin of error you want to halve. About how many people are needed?
1. 1728
2. 864
3. About half as many
A margin of error is 0.08. If the sample size is multiplied by 9, what is the new margin of error?
A random sample of 25 has standard deviation s = 16. With t* = 2.064 (24 df, 95%), find the margin of error for the mean.
A one-sample t interval uses a sample of 5. How many degrees of freedom?
Why is a t critical value used for a confidence interval for a mean from a sample of 40?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 22?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 13?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 35?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 34?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 23?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 11?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 10?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 37?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 26?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 24?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 31?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 30?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 39?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 32?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 12?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 17?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 18?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 27?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 16?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 28?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 20?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 25?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 19?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 14?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 33?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 38?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 21?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 29?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 36?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Why is a t critical value used for a confidence interval for a mean from a sample of 15?
1. Because σ is estimated by s, which adds variability
2. Because n is less than 1,000
3. Because the data are skewed
Independent samples of 100 give p̂₁ = 1/10 and p̂₂ = 6/10. Using z* = 1.96, find the margin of error for p₁ − p₂.
A 95% interval for p₁ − p₂ is (−0.07, 0.08). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.08, 0.06). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.02, 0.04). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.05, 0.06). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.02, 0.02). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.03, 0.01). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.09, 0.08). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.01, 0.03). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.09, 0.07). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.01, 0.09). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.08, 0.07). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.09, 0.03). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.06, 0.01). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.01, 0.07). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.07, 0.01). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.02, 0.03). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.02, 0.06). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.04, 0.07). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.09, 0.04). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.04, 0.04). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.08, 0.08). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.02, 0.09). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.07, 0.03). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.04, 0.01). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.06, 0.04). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.07, 0.04). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.06, 0.02). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.03, 0.06). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.05, 0.01). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.02, 0.07). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.07, 0.09). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.03, 0.03). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.06, 0.09). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.02, 0.05). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.03, 0.08). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.03, 0.07). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.01, 0.04). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.05, 0.04). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.07, 0.06). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.08, 0.09). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.09, 0.09). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.01, 0.06). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.07, 0.07). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.08, 0.01). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.04, 0.05). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.06, 0.03). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.02, 0.08). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.05, 0.07). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.02, 0.01). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
A 95% interval for p₁ − p₂ is (−0.03, 0.09). What does it suggest?
1. No convincing difference: 0 is a plausible value of p₁ − p₂
2. p₁ is larger, since the upper end is positive
3. It proves p₁ = p₂
Two groups have sample means 90 and 58. What is the point estimate of μ₁ − μ₂?

Answers

$\frac{1}{20}$
$48$
A larger sample size
$\frac{49}{1000}$
$\frac{\sqrt{21}}{50} + \frac{3}{10}$
We are 95% confident that the interval from 0.48 to 0.52 captures the true proportion of supporters
The 99% interval
In repeated random sampling, about 90% of the intervals built this way capture the parameter
$\frac{23}{250}$
$\frac{2401}{4}$
1056
$\frac{2}{75}$
$\frac{4128}{625}$
$4$
Because σ is estimated by s, which adds variability
$\frac{49 \sqrt{33}}{2500}$
No convincing difference: 0 is a plausible value of p₁ − p₂
$32$