# Type I and Type II Error

> Source: https://sukruyusufkaya.com/en/glossary/tip-i-ve-tip-ii-hata
> Updated: 2026-05-13T21:11:24.696Z
> Type: glossary
> Category: matematik-istatistik-optimizasyon
**TLDR:** The two fundamental error types in hypothesis testing: false alarm and failing to detect a real effect.

<p>Making decisions in hypothesis testing always involves some risk of error. A Type I error occurs when we incorrectly reject a null hypothesis that is actually true, meaning we detect an effect that does not exist. A Type II error occurs when we fail to detect a real effect and incorrectly retain the null hypothesis. There is a natural trade-off between these two errors; reducing one may sometimes increase the other. Understanding them is critical in medical testing, model selection, A/B testing, and risk-sensitive decision systems.</p>