type II error

statistics

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July 14, 2026

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In statistics, a Type II error occurs when the null hypothesis is accepted, despite it being false. This is a crucial concept within hypothesis testing, a method used to draw conclusions about a population based on sample data.12

Ideally, hypothesis testing correctly rejects a false null hypothesis and accepts a true one. However, errors can occur. A Type I error is rejecting the null hypothesis when it is actually true. In contrast, a Type II error means failing to reject a null hypothesis that should have been rejected. The probability of a Type II error is denoted by β.312

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statistics
Hypothesis testing
_… is actually true, and a type II error corresponds to accepting H₀ when H₀ is false. The probability of making a type I error is denoted by α, and the probability of making a type II error is denoted by β.
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_… is actually true, and a type II error corresponds to accepting H₀ when H₀ is false. The probability of making a type I error is denoted by α, and the probability of making a type II error is denoted by β.
Read More