## Type I and Type II Errors

### Answers

- In this example, there is really a difference in the population between recognition and recall, but you did not find a significant difference in your sample. Failing to reject a false null hypothesis is a Type II error.

- There is no difference in the population, but you found a difference in your sample. A Type I error occurs when a significance test results in the rejection of a true null hypothesis.

- The Type I error rate is affected by the alpha level; the lower the alpha level is, the lower the Type I error rate gets. Alpha is the probability of a Type I error given that the null hypothesis is true.

- The probability of a Type II error is called beta. The probability of correctly rejecting a false null hypothesis equals 1- beta and is called power.

- A Type I error occurs when a significance test results in the rejection of a TRUE null hypothesis.