Who Actually Gets Studied
A population is the entire group you want to understand, while a sample is the subset actually studied. Because studying everyone is impractical, how you sample determines if your findings generalize back to the population.
| Method | How it selects | Generalizability |
|---|---|---|
| Random | Equal chance for all | Strong |
| Stratified | Proportional by subgroup | Strong, protected |
| Convenience | Whoever is easiest to reach | Weak |
Random sampling minimizes systematic bias. Stratified sampling divides the population into strata (age, gender) and samples proportionally. Convenience sampling (like psychology undergrads) is fast and cheap, but creates sampling bias.
Validity and Sample Size
Poor sampling threatens external validity: findings from a biased sample may not hold for the broader population. This fuels the WEIRD-samples critique, where psychology risks over-generalizing from narrow slices of humanity.
Common pitfall: assuming a LARGE sample automatically means a REPRESENTATIVE sample.
Sample size and sampling method are separate issues. A huge convenience sample of 50,000 self-selected online volunteers can still be badly biased, while a smaller, carefully drawn random sample generalizes far better.