(D) When you choose a significance level a, you're setting the probability of a Type I error to exactly a.

This statement is correct. In hypothesis testing, the significance level (\(\alpha\)) represents the probability of making a Type I error, which occurs when you reject a null hypothesis that is actually true. By setting the significance level, you determine the threshold for how extreme the observed data must be in order to reject the null hypothesis. The probability of a Type I error is equal to the chosen significance level (\(\alpha\)). For example, if you choose a significance level of 0.05, you're accepting a 5% chance of making a Type I error.