Random samples, sources of bias and variability of samples from uniform, normal and Bernoulli distributions

What this note covers

1. Population, sample and sampling frame
2. Constructing a reproducible random sample
3. How selection bias enters
4. Procedures that protect randomness
5. Variability across repeated random samples
6. Separating bias from variability
7. Designing a defensible sampling plan
8. Diagnosing sampling claims from evidence

8 sections · 10 key terms & formulas · 6 common mistakes