Distinguish between observational studies and experiments, identify confounding variables, and evaluate the validity of statistical claims.
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?
A
The drug is associated with improvement, but may not cause it
B
The drug caused the improvement in this sample
C
The drug will work for all patients everywhere
D
The improvement could be due to the placebo effect
B
A study finds that students who play musical instruments have higher GPAs. Why doesn't this prove that playing music causes higher GPAs?
A
The sample was too small
B
GPA is not a reliable measure
C
Students with more supportive families may be more likely to both play instruments and study hard
D
The study should have used a placebo
C
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).
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 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.
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.
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