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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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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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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.


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 ...

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