If the p-value in a study is 0.10, what is the probability of committing a Type I error?

• A. 1 in 100
• B. 1 in 20
• C. 1 in 10
• D. 1 in 5

Answer: (C)

The p-value represents how extreme the observed data are under the assumption that the null hypothesis is true. The probability of making a Type I error is the significance level you choose for the test, often denoted alpha. If the p-value is 0.10, that means the smallest alpha at which you would reject the null is 0.10. So, at that threshold, the chance of falsely rejecting the true null—the Type I error rate—would be 0.10, or 1 in 10.

Note that the p-value itself isn’t the Type I error probability in general, but it corresponds to the alpha level at which you would decide to reject in this scenario.