Type I and type II errors

Type I error, or a false positive, is the incorrect rejection of a true null hypothesis in statistical hypothesis testing. A type II error, or a false negative, is the incorrect acceptance of a false null hypothesis.

Source: Wikipedia — Type I and type II errors (CC BY-SA 4.0)