Conceptual Preparation: Statistical Inference

Statistical inference is vulnerable to two types of errors:

• Type I
• Type II

So far, we’ve only talked about the Type I error—rejecting the null hypothesis when it’s true. The Type I error is reflected by $\alpha$—the acceptable Type I error rate—and the p value in hypothesis testing. If a Type I error is the only concern, analysts can merely minimize it to near zero. That, unfortunately, isn’t feasible because of the presence of the Type II error. Type II error is the error of failing to reject the null hypothesis when it’s false.