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.
