Statistics and Probability · Estimation

Sampling and sampling distributions

How a statistic, like a sample mean, itself varies from sample to sample if you repeated the study.

Also known as: sampling distribution of the mean, standard error.

Start a lesson on Sampling and sampling distributions

Learn first

• Central limit theorem: Why the average of almost any large sample ends up looking approximately Normal, regardless of the original distribution's shape.

Leads to

• Point estimation: Using sample data to produce a single best-guess number for an unknown population value.
• Resampling and the bootstrap: Estimating how uncertain a statistic is by repeatedly resampling from the data you already have, instead of relying on a formula.

Related topics

• Resampling and the bootstrap: Estimating how uncertain a statistic is by repeatedly resampling from the data you already have, instead of relying on a formula.