Observational studies, experiments and confounding

About this lesson

Algebra II › Statistical inference

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Observational studies, experiments and confounding

Warm-up

Three quick questions from earlier lessons.

Discover

Cities with more firefighters at a fire have more damage. Do firefighters cause damage?

  1. No, bigger fires explain both
  2. Yes, the data show it

Key idea

Only experiments can show cause and effect.

In an observational study we record what happens without intervening; in an experiment we impose treatments. A confounding variable is related to both the explanatory and the response variable, so its effect cannot be separated. Observational studies show associations, not causation.

Worked example

Students who take music lessons have higher grades.

Observational study
Nobody assigned the lessons.
Possible confounder: family income
Affects both lessons and grades.
Conclusion: association only
To test cause, assign lessons at random.

Your turn, guided

Your turn: 80 volunteers are split at random, 40 per group. How many get the treatment?

4040
Half of 80.

Practice ★

  1. 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
  1. 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

Watch out!

Practice ★★

  1. 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
  2. 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

Exit ticket

Three questions to check you have got it.

  1. 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
  2. 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
  3. 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

Summary card

Studies

  • Observational: record. Experiment: assign.
  • Confounding hides cause in observational data.

Watch out: association is not causation.

End of the lesson

Next lesson: Designing experiments: randomization, replication, blocking Back to the chapter

Answers: Observational studies, experiments and confounding

A

  1. An experiment: the researchers assign the treatment

B

  1. A confounding variable: age affects both shoe size and reading

C

  1. No: other differences between the groups could explain it
  2. No: other differences between the groups could explain it

D

  1. An experiment: the researchers assign the treatment
  2. An experiment: the researchers assign the treatment
  3. An experiment: the researchers assign the treatment

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