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    Difference Between Type I and Type II Error in Statistics

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    Please explain the difference between a Type I and a Type II error when testing a hypothesis.
    Please provide an example of each.

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    https://brainmass.com/statistics/type-i-and-type-ii-errors/difference-type-error-statistics-470226

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    TYPE I ERROR:

    Also called an alpha error. A type I error is a false positive. You make this kind of error when you reject a null hypothesis when it is actually true.

    TYPE II ERROR:

    Also called a beta error. A type II error is a false negative. You make this kind of error when you fail to reject the null hypothesis when you should (i.e. when the ...

    Solution Summary

    This solution explains the difference between Type I and Type II errors when testing a hypothesis and provides an example of each.

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