Type I error

Last revised by Daniel J Bell on 14 Nov 2017

Type I errors (alpha errors, α) occur when we accept that there is a difference between two experimental groups, when in fact, no difference exists.

The threshold for accepting a type I error is the p-value. The traditionally accepted p-value of 0.05 indicates that the researchers are willing to take a ≤5% chance that the outcome of their data showing a difference between two groups was merely due to chance.

If multiple tests are compared, the risk of type I error increases.

Good statistical technique attempts to keep the risk of type I error as low as possible.

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Cases and figures

  • Figure 1: Alpha error
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  • Figure 2: alpha and beta error
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