# statistics

Suppose that a researcher normally uses an alpha level of .01 for hypothesis test, but this time uses an alpha level of .05. What does this change in the alpha level do to the amount of power? What does it do to the risk of a Type I error?

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1. There are two types of error, Type I and type II. Type I (alpha) error is the probability of rejecting Ho when it is really true. Type II (beta) error is the probability of accepting Ho when it is actually false. Power is 1-beta.

Changing alpha from .01 to .05 increases your risk of Type I error and decreases your risk of Type II error, thus increasing power.

I hope this helps. Thanks for asking.

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