Hypothesis testing is a kind of binary classification problem. As we discussed in Section 5.1.3, there are two kinds of error we can make, known as a false positive or type I error, which corresponds to accidentally rejecting the null hypothesis H 0 when it is true, and a false negative or type II error which corresponds to accidentally accepting the null when the alternative is true.
murphyk
commented
3 months ago
Should be