With any hypothesis test, we need to state the null and alternative hypotheses, then determine the level of significance. We’ve already covered these first two steps, and now we want to learn how to calculate the test statistic, which will depend on whether we’re running a two-tail test or a one-tail test.

Read MoreType I error rate is the rejecting the null hypothesis when it’s true, and Type II error rate is the probability of accepting the null hypothesis when it’s false. Type I error is called “alpha,” and Type II error is called “beta.”

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