Problem Solving & Data Analysis Hard
⏱ 12 min 📊 Hard ⭐ Premium

Evaluating Statistical Claims: Studies and Experiments

Distinguish between observational studies and experiments, identify confounding variables, and evaluate the validity of statistical claims.

Before you read
Answer first — see what you already know.

Researchers randomly assign 100 patients to receive either a new medication or a placebo. After 8 weeks, the medication group shows significantly greater improvement. Which conclusion is valid?

Check your answer
Answer:

B

Before you read
Answer first — see what you already know.

A study finds that students who play musical instruments have higher GPAs. Why doesn't this prove that playing music causes higher GPAs?

Check your answer
Answer:

C

Theory

Observational Studies vs. Experiments

Observational study: Researchers observe and record data without intervening. Example: Comparing test scores of students who choose to attend tutoring vs. those who don't.

Experiment: Researchers actively assign treatments to subjects. Example: Randomly assigning students to tutoring or no tutoring.

Key difference: Only experiments with random assignment can establish cause and effect. Observational studies can only show association (correlation).

Comparing studiesStudySample SizeMethodBias?A50VolunteerYesB500RandomNo
Larger random samples produce more reliable results
Theory

Confounding Variables

A confounding variable (lurking variable) is a variable that influences both the explanatory and response variables, creating a misleading association.

Example: People who own boats tend to have higher incomes. It looks like boats \to wealth, but the confounding variable is overall wealth (wealthy people buy both boats and other expensive things).

Random assignment in experiments helps control for confounders by distributing them equally across groups.

Example 1

A study finds that coffee drinkers have higher rates of heart disease. Does coffee cause heart disease?

This is an observational study (coffee wasn't randomly assigned).

Possible confounder: Coffee drinkers might also smoke more, be more stressed, or sleep less.

We can't conclude causation without controlling for confounders.

Not necessarily — confounding variables could explain the association.

Continue this lesson in the app

2 more sections including examples, practice problems, and step-by-step solutions.

Try NovaMath Free
experimental-designcausationsat-problem-solving

Ready to ace the SAT?

Try NovaMath free — AI tutoring, 115 lessons, 2,400+ exercises.

Try NovaMath Free