WANI Dictionary

Type I error

In statistics, a type I error refers to a false positive error, in which a test result incorrectly indicates the presence of a condition.

For example, in a group comparison, a type I error indicates the incorrect rejection of the null hypothesis. There are no significant differences between the groups, but some "false significances" are detected.

On the other hand, a type II error refers to a false negative error, in which a test result incorrectly indicates the absence of a condition.

Definitions in the literature

• If we actually obtain data that lead us to reject the null hypothesis of no effect when the null hypothesis of no effect is true, statisticians say that we have made a Type I error [1].