Topic C7 — Sampling

Table of contents
  1. Topic C7 — Sampling
    1. Sampling methods
      1. Simple random sampling
      2. Stratified sampling
      3. Cluster sampling
    2. Sampling distribution

Sampling methods

Simple random sampling

  • All observation have the same probability of being sampled

Stratified sampling

  • Dividing dataset in mutually exclusive + collectively exhaustive stratas.
  • Sample x% of each strata
  • Advantage
    • precision
    • every strata represented

Cluster sampling

  • Dividing dataset in mutually exclusive + collectively exhaustive clusters
  • Randomly select some clusters
  • Advantage: cost

Sampling distribution

  • Drawing samples gives you a single distribution of values of X
  • Each sample produces a sample mean
  • If you draw multiple samples, you get multiple means, called a sampling distribution

Will converge to the mean of pop $ \mu $

Standard error of sample mean $\frac{\sigma}{\sqrt{n}}$

If the population is normal, then the sampling distribution is also normal, thus we can standardiye it.