Type I and type II errors

In statistics, type I and type II errors are errors that happen when a coincidence occurs while doing statistical inference, which leads to one making the wrong conclusion. One makes a Type I error when the original hypothesis is rejected, when it is actually true. Conversely, one makes a Type II error when the original hypothesis is accepted, when it is actually false. The probability of type I error is often written as $\alpha$, while the probability of type II error is written as $\beta$.

Related pages

• Alpha
• Beta
• False positives and false negatives
• Power of a test

References

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