Understanding Type I and Type II errors
In hypothesis testing, there is always a chance of making errors:
- A Type I error occurs when we reject the null hypothesis when it is true (this is also known as a false positive)
- A Type II error occurs when we fail to reject the null hypothesis when it is false (this is also known as a false negative):
Figure 8.7: Type I error vs. Type II
Understanding the nuances and implications of Type I and Type II errors is fundamental to hypothesis testing. In Figure 8.7, we see that Type I Error occurs at the intersection of the null hypothesis being true, and the action of rejecting the null hypothesis. This is similar to a pregnancy test coming back positive when the woman is not in fact pregnant (also known as a false positive result).
Simiarly, Type II Errors occur when the null hypothesis is false, but incorrectly fails to reject the null hypothesis. This is like having a pregnancy test that tells...
