Errors in Statistical Decision-Making
Type I Error — \(\alpha\)
Rejecting \(H_0\) when it is true
= False Positive = "false alarm"
Probability of this error = \(\alpha\) = significance level
Type II Error — \(\beta\)
Failing to reject \(H_0\) when it is false
= False Negative = "missed detection"
Decision table
| \(H_0\) true | \(H_0\) false | |
|---|---|---|
| Reject \(H_0\) | Type I Error (\(\alpha\)) | Correct decision |
| Fail to reject \(H_0\) | Correct decision | Type II Error (\(\beta\)) |