How do you remember Type I versus Type II error without second-guessing yourself?

Start with the action, not the Roman numeral.

• Type I error: you rejected the null hypothesis, but the null was actually true.
• Type II error: you failed to reject the null hypothesis, but the null was actually false.

A practical way to anchor it is:

• Type I = false alarm
• Type II = missed detection

Imagine fictional lender Stone Harbor Credit tests whether its new underwriting filter reduces defaults.

• If the firm rejects the null and rolls out the filter even though it does not really help, that is a false alarm, so Type I.
• If the firm fails to reject the null and cancels a filter that actually would have reduced defaults, that is a missed detection, so Type II.

The significance level controls the probability of a Type I error. It does not directly equal the probability of a Type II error.

If you remember the decision you took, the labels become much easier to recover under pressure.