Type 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.”

Read MoreIt’s important to know whether we’re talking about a population or a sample, because in this section we’ll be talking about variance and standard deviation, and we’ll use different formulas for variance and standard deviation depending on whether we’re using data from a population or data from a sample.

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