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.