
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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![**Hypothesis Testing for Aircraft Altimeter Errors**
**Test the given claim:** Assume that a simple random sample is selected from a normally distributed population. Use either the P-value method or the traditional method of testing hypotheses.
**Scenario:**
Company A uses a new production method to manufacture aircraft altimeters. A simple random sample of new altimeters resulted in errors listed below. Use a 0.05 level of significance to test the claim that the new production method has errors with a standard deviation greater than 32.2 ft, which was the standard deviation for the old production method. If it appears that the standard deviation is greater, does the new production method appear to be better or worse than the old method? Should the company take any action?
**Error Data Sample:**
-44, 76, -25, -70, -40, 11, 19, 54, -54, -108, -108
**Steps:**
1. **Find the test statistic:**
\[
\chi^2 = \_\_
\]
(Round to two decimal places as needed.)
2. **Determine the critical value(s):**
\[
\text{The critical value(s) is/are } \_\_
\]
(Use a comma to separate answers as needed. Round to two decimal places as needed.)
3. **Decision Rule:**
- Since the test statistic is **greater than** the critical value(s),
- **Reject \( H_0 \):**
There is **sufficient** evidence to support the claim that the new production method has errors with a standard deviation greater than 32.2 ft.
- The variation appears to be **greater** than in the past, so the new method appears to be **worse** because there will be larger errors.
### Diagrams and Graphs
- **Explanation:** No explicit diagrams or graphs are present in the image. The focus is on calculating the test statistic and determining critical values for hypothesis testing based on provided data.
The company should consider revisiting the production method to reduce errors.](https://content.bartleby.com/qna-images/question/381c88fc-86c8-43b0-81f2-55a4fcd1abcd/d438930e-abba-4604-9663-3c5a71e471e0/h84iori9_thumbnail.jpeg)
Transcribed Image Text:**Hypothesis Testing for Aircraft Altimeter Errors**
**Test the given claim:** Assume that a simple random sample is selected from a normally distributed population. Use either the P-value method or the traditional method of testing hypotheses.
**Scenario:**
Company A uses a new production method to manufacture aircraft altimeters. A simple random sample of new altimeters resulted in errors listed below. Use a 0.05 level of significance to test the claim that the new production method has errors with a standard deviation greater than 32.2 ft, which was the standard deviation for the old production method. If it appears that the standard deviation is greater, does the new production method appear to be better or worse than the old method? Should the company take any action?
**Error Data Sample:**
-44, 76, -25, -70, -40, 11, 19, 54, -54, -108, -108
**Steps:**
1. **Find the test statistic:**
\[
\chi^2 = \_\_
\]
(Round to two decimal places as needed.)
2. **Determine the critical value(s):**
\[
\text{The critical value(s) is/are } \_\_
\]
(Use a comma to separate answers as needed. Round to two decimal places as needed.)
3. **Decision Rule:**
- Since the test statistic is **greater than** the critical value(s),
- **Reject \( H_0 \):**
There is **sufficient** evidence to support the claim that the new production method has errors with a standard deviation greater than 32.2 ft.
- The variation appears to be **greater** than in the past, so the new method appears to be **worse** because there will be larger errors.
### Diagrams and Graphs
- **Explanation:** No explicit diagrams or graphs are present in the image. The focus is on calculating the test statistic and determining critical values for hypothesis testing based on provided data.
The company should consider revisiting the production method to reduce errors.
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