Sampling is the process of taking a smaller group of subjects/scores from a larger population. In statistical inference, we test hypotheses about the population using samples. The sample is used to estimate a parameter in the larger population. Statistical inference assumes that the sample is selected randomly from the population.

Why Is This Important?

All inferential statistics use random samples drawn from a larger population for hypothesis tests. In order to accurately conduct our tests, we need to understand sampling distributions and their role in hypothesis testing.

A population distribution is presented below.