What is a Type I error?

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Multiple Choice

What is a Type I error?

A Type I error is a false positive: you reject the null hypothesis even though it is true. The null usually states that there is no effect or no difference, so rejecting it leads you to conclude something real exists when it doesn’t. The chance of making this error is set by the significance level (alpha) before the test (for example, 0.05 means up to 5% of the time you could incorrectly reject a true null). The other common error is failing to detect a real effect (a Type II error), which is different from the situation described here.

A Type I error is a false positive: you reject the null hypothesis even though it is true. The null usually states that there is no effect or no difference, so rejecting it leads you to conclude something real exists when it doesn’t. The chance of making this error is set by the significance level (alpha) before the test (for example, 0.05 means up to 5% of the time you could incorrectly reject a true null). The other common error is failing to detect a real effect (a Type II error), which is different from the situation described here.

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