# Type I and Type II Errors

*Math & Statistics — Finicade finance glossary*

A Type I error rejects a true null hypothesis — a false positive. A Type II error fails to reject a false one — a false negative. The two trade off against each other: demanding stronger evidence cuts false positives and raises false negatives. Which matters more is a business decision, not a statistical one, since a missed fraud and a wrongly frozen account have very different costs.

**Also known as:** false positive, false negative, type 1 error, type 2 error

**Related terms:** [Hypothesis Test](https://finicade.com/glossary/hypothesis-test), [Statistical Power](https://finicade.com/glossary/statistical-power), [P-Value](https://finicade.com/glossary/p-value), [Null Hypothesis](https://finicade.com/glossary/null-hypothesis), [Backtesting](https://finicade.com/glossary/backtesting)

Source: https://finicade.com/glossary/type-i-and-type-ii-errors