## What is worse a Type 1 or Type 2 error?

A Type I error, on the other hand, is an error in every sense of the word. A conclusion is drawn that the null hypothesis is false when, in fact, it is true. Therefore, Type I errors are generally considered more serious than Type II errors.

## What are the type I and type II decision errors costs?

A Type I is a false positive where a true null hypothesis that there is nothing going on is rejected. A Type II error is a false negative, where a false null hypothesis is not rejected – something is going on – but we decide to ignore it.

**How do you determine Type 2 error?**

Recall that in hypothesis testing you can make two types of errors • Type I Error – rejecting the null when it is true. Type II Error – failing to reject the null when it is false. The probability of a Type I Error in hypothesis testing is predetermined by the significance level.

### How does sample size affect Type 2 error?

Type II errors are more likely to occur when sample sizes are too small, the true difference or effect is small and variability is large. The probability of a type II error occurring can be calculated or pre-defined and is denoted as β.