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Null & Alternate Hypothesis and Error type

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A consumer advocacy group is doing a large study on car rental practices. Among other things, the consumer group would like to do a statistical test regarding the mean monthly mileage, , of cars rented in the U.S. this year. The consumer group has reason to believe that the mean monthly mileage of cars rented in the U.S. this year is less than last year's mean, which was 2850 miles.
The group plans to do a statistical test regarding the value of 2850 chooses a random sample of monthly mileages and computes the mean of the sample to be miles and the standard deviation to be miles.
Based on this information, answer the questions below.
Answer the following:
-H0: mu = (less than, greater than or equal to, greater than, less than or equal to, not equal to, equal to) (2850, 850,2715)
-H1: mu= (less than, greater than or equal to, greater than, less than or equal to, not equal to, equal to) (2850, 850,2715)
In the context of this test, what Type II error?
-A Type I error is (rejecting, failing to reject) the hypothesis that mu is (less than, greater than or equal to, greater than, less than or equal to, not equal to, equal to) (2850, 850,2715) when, in fact, mu is (less than, greater than or equal to, greater than, less than or equal to, not equal to, equal to) (2850, 850,2715).
-Suppose that the group decides not to reject the null hypothesis. What sort of error might it be making? (Type I, Type II)

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Answer the following:
H0: mu = (equal to) (2850)
H1: mu= (less than) (2850)
In the ...

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This post answers multiple-choice questions on setting the null and alternative hypothesis and identifying the correct error type i.e. Type I and Type II.

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Statistics: Setting up null and alternative hypotheses, interpreting Type I and Type II errors

We know from past research that very satisfied customers give the XYZ-Box video game system a satisfaction rating on our rating scale that is at least 42. Suppose that the manufacturer of the XYZ-Box wishes to use a random sample of 65 satisfaction ratings to provide evidence supporting the claim that the mean satisfaction rating for the XYZ-box exceeds 42.

a. Letting m represent the mean satisfaction rating for the XYZ-Box, set up the null and alternative hypotheses needed if we wish to attempt to provide evidence supporting the claim that m exceeds 42.

b. In the context of this situation, interpret making a Type I error; interpret making a Type II error.

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