(a) What are the null hypothesis H, and the alternative hypothesis H, that should be used for the test? (b) Suppose that the group decides not to reject the null hypothesis. What sort of error might it be making? (Choose one) ▼ (c) Suppose the true mean monthly mileage of cars rented in the U.S. this year is 2915. Fill in the blanks to describe a Type II error. A Type II error would be (Choose one) the hypothesis that u is (Choose one) (Choose one) when, in fact,H is (Choose one)

MATLAB: An Introduction with Applications
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Chapter1: Starting With Matlab
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A consumer advocacy group is conducting a large study on car rental practices. The group aims to evaluate the mean monthly mileage, denoted as \( \mu \), of cars rented in the U.S. this year. They suspect that the mean mileage this year is greater than last year's average of 2750 miles.

The group will perform a statistical test to investigate the value of \( \mu \). They have selected a random sample of monthly mileages and calculated the sample mean to be 2900 miles, with a standard deviation of 700 miles.

Based on this information, the group needs to address the following:

(a) **What are the null hypothesis (\( H_0 \)) and the alternative hypothesis (\( H_1 \)) that should be used for the test?**
   - \( H_0: \mu = 2750 \)
   - \( H_1: \mu > 2750 \)

(b) **Suppose that the group decides not to reject the null hypothesis. What sort of error might it be making?**
   - The group might be making a Type II error.

(c) **Suppose the true mean monthly mileage of cars rented in the U.S. this year is 2915 miles. Fill in the blanks to describe a Type II error.**
   - A Type II error would be failing to reject the hypothesis that \( \mu = 2750 \) when, in fact, \( \mu = 2915 \).

### Explanation of Diagram:

On the right side of the text, there is a diagram displaying various hypothesis test notations:
- \( \mu \): population mean
- \( \bar{x} \): sample mean
- Inequality signs representing potential relationships between \( \mu \) and 2750.

These symbols are used to help formulate hypotheses and interpret statistical results in hypothesis testing.
Transcribed Image Text:A consumer advocacy group is conducting a large study on car rental practices. The group aims to evaluate the mean monthly mileage, denoted as \( \mu \), of cars rented in the U.S. this year. They suspect that the mean mileage this year is greater than last year's average of 2750 miles. The group will perform a statistical test to investigate the value of \( \mu \). They have selected a random sample of monthly mileages and calculated the sample mean to be 2900 miles, with a standard deviation of 700 miles. Based on this information, the group needs to address the following: (a) **What are the null hypothesis (\( H_0 \)) and the alternative hypothesis (\( H_1 \)) that should be used for the test?** - \( H_0: \mu = 2750 \) - \( H_1: \mu > 2750 \) (b) **Suppose that the group decides not to reject the null hypothesis. What sort of error might it be making?** - The group might be making a Type II error. (c) **Suppose the true mean monthly mileage of cars rented in the U.S. this year is 2915 miles. Fill in the blanks to describe a Type II error.** - A Type II error would be failing to reject the hypothesis that \( \mu = 2750 \) when, in fact, \( \mu = 2915 \). ### Explanation of Diagram: On the right side of the text, there is a diagram displaying various hypothesis test notations: - \( \mu \): population mean - \( \bar{x} \): sample mean - Inequality signs representing potential relationships between \( \mu \) and 2750. These symbols are used to help formulate hypotheses and interpret statistical results in hypothesis testing.
Expert Solution
Step 1

The type I error is defined as the rejecting the null hypothesis when actually it is true.

The type II error is defined as the accepting the null hypothesis when alternative is true.

 

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