12. Types of Errors - Part III

Type I Errors

Type I errors have the following features:

1. You should set up your null and alternative hypotheses, so that the worst of your errors is the type I error.
2. They are denoted by the symbol \alpha .
3. The definition of a type I error is: Deciding the alternative ( H_1 ) is true, when actually ( H_0 ) is true.
4. Type I errors are often called false positives .

Type II Errors

1. They are denoted by the symbol \beta .
2. The definition of a type II error is: Deciding the null ( H_0 ) is true, when actually ( H_1 ) is true.
3. Type II errors are often called false negatives .

Parachute Example

This example let you see one of the most extreme cases of errors that might be committed in hypothesis testing. In a type I error an individual died. In a type II error, you lost 30 dollars.

In the hypothesis tests you build in the upcoming lessons, you will be able to choose a type I error threshold, and your hypothesis tests will be created to minimize the type II errors after ensuring the type I error rate is met.