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

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

• A. Confidence interval
• B. Type II error
• C. Power
• D. Type I error

Answer: (D)

When you reject the null hypothesis even though it is true, you’re making a Type I error—a false positive. In hypothesis testing, the null typically states that there is no effect or no difference. The test is designed so that, if the null is true, you still have a small chance (the chosen significance level, alpha) of incorrectly concluding there is an effect. This risk is exactly what a Type I error represents. This is different from a Type II error, which happens when you fail to reject the null even though there is a real effect (a false negative). Power, on the other hand, is the probability of correctly rejecting a false null, i.e., avoiding Type II errors. A confidence interval relates to the range of plausible values for a parameter and is connected to the same idea of uncertainty but is not itself an error category.

When you reject the null hypothesis even though it is true, you’re making a Type I error—a false positive. In hypothesis testing, the null typically states that there is no effect or no difference. The test is designed so that, if the null is true, you still have a small chance (the chosen significance level, alpha) of incorrectly concluding there is an effect. This risk is exactly what a Type I error represents.

This is different from a Type II error, which happens when you fail to reject the null even though there is a real effect (a false negative). Power, on the other hand, is the probability of correctly rejecting a false null, i.e., avoiding Type II errors. A confidence interval relates to the range of plausible values for a parameter and is connected to the same idea of uncertainty but is not itself an error category.