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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 ...