Recognize sampling methods, bias, and variability; interpret study designs at a high level.
Use a random sample from the full population to reduce selection bias.
Core Idea
A good study starts with a representative sample. Random selection reduces bias, while convenience samples and volunteer responses can distort the result before any data are analyzed.
Understanding
Rule: Sampling method matters because bad input produces misleading conclusions, even with correct calculations. A convenience sample is easy to collect but may overrepresent one type of person. A voluntary response sample often attracts people with stronger opinions. A random sample from the full population is usually the best way to reduce selection bias.
At a high level, you should also notice whether the study design allows comparison, random assignment, or only observation. ACT questions in this area are usually about whether the evidence is fair and representative, not about advanced statistical tests.
Step by Step
- Decide whether the sample is random, convenience-based, or voluntary.
- Check whether the sample represents the full population.
- Choose the design that best reduces selection bias.
Misconceptions
- Assuming a large sample is automatically unbiased.
- Treating volunteers as if they represent the full population.
- Confusing random sampling with random assignment.
Worked Example
A principal wants to estimate the average number of hours students at a high school sleep on school nights. Which study design is least likely to produce a biased sample?
Select an answer to see the explanation