Errors in Hypothesis Testing

Hypothesis tests do not provide certainty, only an indication of the strength of the evidence. In essence, "alpha" =0.05 is an error rate of 5% when rejecting the null hypothesis and accepting the alternative hypothesis. This is referred to as a Type I error. In contrast, a Type II error occurs when there really is a difference, but we fail to reject the null hypothesis.

Truth H0 Not Rejected
(Insufficient Evidence of a Difference)
H0 Rejected
(Difference)
H0 true Correct Type I error
H0 false Type II error Correct

 Type I Error: Concluding that there is a difference when there isn't

Type II Error: Concluding no difference when there really is one.