Which error occurs when the null hypothesis is true but you reject it?

Which error occurs when the null hypothesis is true but you reject it?

• A. Type I error
• B. Type II error
• C. Regression toward the mean
• D. Power

Answer: (A)

Type I error occurs when the null hypothesis is true, yet you reject it. In hypothesis testing, the null represents no effect or no difference. If your data lead you to conclude there is an effect when there actually isn’t one, you’ve made a false positive. The likelihood of this happening is set by your chosen significance level (often 0.05), which you accept as the chance of making this error. By contrast, Type II error is failing to reject the null when it is false (a false negative). Regression toward the mean is a general variability phenomenon where extreme results tend to move closer to the average on repeated measurements. Power is the probability of correctly rejecting a false null hypothesis, not about the error that occurs when the null is true.

Type I error occurs when the null hypothesis is true, yet you reject it. In hypothesis testing, the null represents no effect or no difference. If your data lead you to conclude there is an effect when there actually isn’t one, you’ve made a false positive. The likelihood of this happening is set by your chosen significance level (often 0.05), which you accept as the chance of making this error. By contrast, Type II error is failing to reject the null when it is false (a false negative). Regression toward the mean is a general variability phenomenon where extreme results tend to move closer to the average on repeated measurements. Power is the probability of correctly rejecting a false null hypothesis, not about the error that occurs when the null is true.