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    Selection of a tail test impact

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    1) How might the selection of a given tail test impact the Type I or II error, if any?

    2) If the problem itself is not yet stated how might a researcher know which type of -tail test to use?

    3) Might there be instances where a test is looking for a section of the area under the curve and not just the extreme ends?

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    Solution Preview

    General Questions?
    1) How might the selection of a given -tail test impact the Type I or II error, if any?

    Solution:

    Choosing an alpha level is tricky because it sets the level at which we will reject the null hypothesis. And there is a chance that the higher this value is, the greater the chance that we will falsely reject a true Ho.
    To give you an analogy, in a court of law, we assume people are innocent (the null hypothesis) until proven guilty.
    A Type I error would be finding an innocent man guilty.
    A Type II error would be letting a guilty man go free.
    By decreasing our error or alpha level, we will increase the chance of a ...

    Solution Summary

    The solution of a tail test is analyzed in the following solution.

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