errors (types I and II)

n. In using inferential statistics error it is possible to make an error by rejecting the null hypothesis when it is true; the false positive result is called a type I error. It is possible to make an error by failing to reject the null hypothesis when it is false; this is called a type II error. Type I error is associated with random error and setting a criterion statistic too low, while type II error is associated with a lack of statistical power in a research design.