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Type I and type II Errors, Statistical Significance

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Question 1:
What is a type I and type II errors in hypothesis testing? What would be examples of each? Explain

Question 2:
What is the difference between statistical significance and practical significance? Why is statistical significance not necessarily of practical important difference to a business decision? Provide an example of this.

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The expert determines what a type I and type II errors in hypothesis testing are. A complete, neat and step-by-step solutions are provided in the attached file.

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Question1:
What is a type I and type II errors in hypothesis testing? What would be examples of each? Explain.

Type I error (the false positive) is the error of rejecting the null hypothesis when it is actually true
(For example, as in a student accused of copying in an examination when she really did not)
Type II error (the false negative) is the error of failing to reject the null hypothesis given that the alternative hypothesis is actually true (For example, as in a student who did actually copy in an examination being let off).
In a Table form:
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