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# Type I and Type II Errors

Remember that the purpose of the hypothesis test is to verify the validity of a claim about a population based on a single sample. Because we are relying on a sample, we expose ourselves to the risk that our conclusions about the population will be wrong.

Using the golf ball example, suppose that my sample falls within the “Reject H0” region of the last figure. That is, according to the sample, my golf ball increases distance off the tee by more than 20 yards. But what if the true population mean is actually much less than 20 yards? This can occur primarily because of sampling error, which I discussed in Chapter 12. This type of error, when we reject H0 when in reality it’s true, is known as a Type I error. The ...

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