Type I and II Errors

Choosing significance to minimize risk

Hypothesis testing seeks to determine if the means or variances are the same or different at some level of confidence. Since we can never be totally confident, it is possible to encounter two types of errors:

  • Type I error - Reject a null hypothesis that is true (Producer's Risk)
  • Type II error - Not reject a null hypothesis that is false (Consumer's Risk)

Choose a confidence (or significance) level that will minimize the risk associated with these errors.

  H0 is True (not different) H0 is False (different)
Fail to Reject H0 Correct Type II Error
- Consumer's Risk
Reject H0 Type I Error
- Producer's Risk
Correct

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