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Alpha and Error in Statistical Tests

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If we decrease the level of significance a (alpha) from 0.05 to 0.01, that means we are:

A. More willing to accept a type II error;
B. More willing to accept a type I error;
C. Less willing to accept a type I error;
D. None of the above.

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A type I error is a false positive and happens when you reject the null hypothesis when it is, in fact, true. To view it another way, you make a type I error when you ...

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