*Type I Error*

*Type I Error*

It has become part of the statistical hypothesis testing culture.

- It is a longstanding convention.
- It reflects a concern over making type I errors (i.e., wanting to avoid the situation where you reject the null when it is true, that is, wanting to avoid “false positive” errors).
- If you set the significance level at .05, then you will only reject a true null hypothesis 5% or the time (i.e., you will only make a type I error 5% of the time) in the long run.

Good