## Question 564:

1## Answer:

No answer provided yet.Making a Type I error is saying there is a difference when in fact no difference exists. You can also say, incorrectly rejecting the null hypothesis. The maximum acceptable probability of committing a Type I is called alpha and is usually set at .05. For example, you might sample two classes each of which is given a different teaching method. If you said there are higher test scores for one teaching method, but if in fact there isn't a difference, then you committed a Type I error.

A Type II error is failing to say there is a difference when one actually exists. This would be failing to reject the null hypothesis when you should have. The maximum acceptable probability of committing a Type II is called beta. We usually speak in terms of Power, which is 1-beta. So the ideal power for a study is .80, or beta of .20.

Now to the questions:

- No error: There is no difference and we say there is no difference.
- Type I error: We rejected the null hypothesis, but it is in fact true.
- Type II error. We failed to reject a null hypothesis that is false
- No error. There is a difference and we say there is a difference.