FILE SELECTED // FILE 00
Type I and Type II Errors
“A test can raise a false alarm or miss a real signal; reducing both comes at a cost.”
01 / SUMMARY
In short
In hypothesis testing, Type I means rejecting a true null; Type II means failing to reject a false null. Their probabilities and consequences depend on the specific decision and scenario.
03 / SCENE
In the wild
A smoke alarm sounding without fire gives a false alarm; staying silent during a fire makes the opposite error.
04 / LIMIT
The limit
Type I is not always the graver mistake, and non-rejection does not prove there is no effect.
FINAL NOTE
What remains
Define which error matters more before setting a decision threshold.