MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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### Statistical Hypothesis Testing Example: Hospital Admissions Due to Motor Vehicle Crashes

Researchers collected data on the numbers of hospital admissions resulting from motor vehicle crashes, with results given for Fridays on the 6th of a month and Fridays on the following 13th of the same month. They used a 0.05 significance level to test the claim that when the 13th day of a month falls on a Friday, the numbers of hospital admissions from motor vehicle crashes are not affected.

#### Data:
- **Friday the 6th:** 10, 6, 12, 12, 4, 5
- **Friday the 13th:** 14, 12, 14, 11, 6, 12

#### Hypotheses for the Test:
- **Null Hypothesis (H₀):** μd = 0
- **Alternative Hypothesis (H₁):** μd ≠ 0  
Where μd is the mean of the differences in numbers of hospital admissions from motor vehicle crashes for the population of all pairs of data.

#### Calculation of the Test Statistic:
The formula for the test statistic is:

\[ t = \frac{\bar{d}}{s/\sqrt{n}} \]

(Details for calculations to be filled in by students rounding to three decimal places as needed.)

#### Critical Values:
Select the correct critical value based on the significance level:

- **Option A:** The critical value is t = [user to fill]
- **Option B:** The critical values are t = ± [user to fill]

#### Result of the Test:
Choose the correct conclusion:

- **A:** There is sufficient evidence to warrant rejection of the claim of no effect. Hospital admissions do not appear to be affected.
- **B:** There is not sufficient evidence to warrant rejection of the claim of no effect. Hospital admissions do not appear to be affected.
- **C:** There is not sufficient evidence to warrant rejection of the claim of no effect. Hospital admissions appear to be affected.
- **D:** There is sufficient evidence to warrant rejection of the claim of no effect. Hospital admissions appear to be affected. 

Students are encouraged to fill in the calculations, determine the critical values, and conclude based on their results. This exercise guides through applying statistical hypothesis testing to real-world scenarios involving public health and safety.
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Transcribed Image Text:### Statistical Hypothesis Testing Example: Hospital Admissions Due to Motor Vehicle Crashes Researchers collected data on the numbers of hospital admissions resulting from motor vehicle crashes, with results given for Fridays on the 6th of a month and Fridays on the following 13th of the same month. They used a 0.05 significance level to test the claim that when the 13th day of a month falls on a Friday, the numbers of hospital admissions from motor vehicle crashes are not affected. #### Data: - **Friday the 6th:** 10, 6, 12, 12, 4, 5 - **Friday the 13th:** 14, 12, 14, 11, 6, 12 #### Hypotheses for the Test: - **Null Hypothesis (H₀):** μd = 0 - **Alternative Hypothesis (H₁):** μd ≠ 0 Where μd is the mean of the differences in numbers of hospital admissions from motor vehicle crashes for the population of all pairs of data. #### Calculation of the Test Statistic: The formula for the test statistic is: \[ t = \frac{\bar{d}}{s/\sqrt{n}} \] (Details for calculations to be filled in by students rounding to three decimal places as needed.) #### Critical Values: Select the correct critical value based on the significance level: - **Option A:** The critical value is t = [user to fill] - **Option B:** The critical values are t = ± [user to fill] #### Result of the Test: Choose the correct conclusion: - **A:** There is sufficient evidence to warrant rejection of the claim of no effect. Hospital admissions do not appear to be affected. - **B:** There is not sufficient evidence to warrant rejection of the claim of no effect. Hospital admissions do not appear to be affected. - **C:** There is not sufficient evidence to warrant rejection of the claim of no effect. Hospital admissions appear to be affected. - **D:** There is sufficient evidence to warrant rejection of the claim of no effect. Hospital admissions appear to be affected. Students are encouraged to fill in the calculations, determine the critical values, and conclude based on their results. This exercise guides through applying statistical hypothesis testing to real-world scenarios involving public health and safety.
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