Size (statistics)

In statistics, the size of a test is the probability of falsely rejecting the null hypothesis. That is, it is the probability of making a type I error. It is denoted by the Greek letter α (alpha).

For a simple hypothesis,

$\alpha =P({\text{test rejects }}H_{0}\mid H_{0}).$

In the case of a composite null hypothesis, the size is the supremum over all data generating processes that satisfy the null hypotheses.

$\alpha =\sup _{h\in H_{0}}P({\text{test rejects }}H_{0}\mid h).$

A test is said to have significance level $\alpha$ if its size is less than or equal to $\alpha$. In many cases the size and level of a test are equal.