Salam Academy
WST03 · Module

Sampling

2 subtopics≈ 70 min in total
  1. Sampling and unbiased estimates

    We usually can't measure a whole population, so we measure a random sample and estimate. The sample mean estimates μ\mu fairly, but for the variance we divide by n−1n-1, not nn, to stop the estimate coming out too small on average.

    ≈ 35 min
  2. The sample mean and the Central Limit Theorem

    The mean of a random sample is itself a random variable. It is centred on μ\mu, its spread shrinks like σn\dfrac{\sigma}{\sqrt n}, and for large samples it is approximately normal whatever the population looks like.

    ≈ 35 min