Test the claim that the proportion of men who own cats is significantly different than the proportion of women who own cats at the 0.01 significance level. The null and alternative hypothesis would be: Ho: PM = PF Ho: PM = HF Ho: PM = PF Ho: PM = F Ho: M = HF Ho: PM = PF H₁:PM PF H₁ μM > μF H₁:pm PF O O O O O The test is: right-tailed two-tailed O O Based on a sample of 60 men, 40% owned cats Based on a sample of 80 women, 50% owned cats The test statistic is: The p-value is: left-tailed O Based on this we: O Reject the null hypothesis O Fail to reject the null hypothesis (to 2 decimals) (to 2 decimals)
Test the claim that the proportion of men who own cats is significantly different than the proportion of women who own cats at the 0.01 significance level. The null and alternative hypothesis would be: Ho: PM = PF Ho: PM = HF Ho: PM = PF Ho: PM = F Ho: M = HF Ho: PM = PF H₁:PM PF H₁ μM > μF H₁:pm PF O O O O O The test is: right-tailed two-tailed O O Based on a sample of 60 men, 40% owned cats Based on a sample of 80 women, 50% owned cats The test statistic is: The p-value is: left-tailed O Based on this we: O Reject the null hypothesis O Fail to reject the null hypothesis (to 2 decimals) (to 2 decimals)
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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![**Hypothesis Testing for Cat Ownership Proportions**
Test the claim that the proportion of men who own cats is significantly different from the proportion of women who own cats at the 0.01 significance level.
**The null and alternative hypotheses would be:**
- \( H_0: p_M = p_F \)
- \( H_1: p_M \neq p_F \)
- \( H_0: \mu_M = \mu_F \)
- \( H_1: \mu_M > \mu_F \)
- \( H_0: p_M = p_F \)
- \( H_1: p_M < p_F \)
- \( H_0: \mu_M = \mu_F \)
- \( H_1: \mu_M \neq \mu_F \)
- \( H_0: \mu_M = \mu_F \)
- \( H_1: \mu_M < \mu_F \)
- \( H_0: p_M = p_F \)
- \( H_1: p_M > p_F \)
**The test is:**
- Right-tailed
- Two-tailed
- Left-tailed
**Sample Data:**
- Based on a sample of 60 men, 40% owned cats.
- Based on a sample of 80 women, 50% owned cats.
**Calculations:**
- The test statistic is: [ ] (to 2 decimals)
- The p-value is: [ ] (to 2 decimals)
**Conclusion:**
Based on this, we:
- Reject the null hypothesis
- Fail to reject the null hypothesis
This setup guides you through testing proportions to see if there's a significant difference between two groups at a specified significance level.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fee710977-90c8-4f84-9cb1-1102aa3efb9b%2F75da124f-fbe8-41da-b502-cfdac0c88ee9%2Feonzkil_processed.jpeg&w=3840&q=75)
Transcribed Image Text:**Hypothesis Testing for Cat Ownership Proportions**
Test the claim that the proportion of men who own cats is significantly different from the proportion of women who own cats at the 0.01 significance level.
**The null and alternative hypotheses would be:**
- \( H_0: p_M = p_F \)
- \( H_1: p_M \neq p_F \)
- \( H_0: \mu_M = \mu_F \)
- \( H_1: \mu_M > \mu_F \)
- \( H_0: p_M = p_F \)
- \( H_1: p_M < p_F \)
- \( H_0: \mu_M = \mu_F \)
- \( H_1: \mu_M \neq \mu_F \)
- \( H_0: \mu_M = \mu_F \)
- \( H_1: \mu_M < \mu_F \)
- \( H_0: p_M = p_F \)
- \( H_1: p_M > p_F \)
**The test is:**
- Right-tailed
- Two-tailed
- Left-tailed
**Sample Data:**
- Based on a sample of 60 men, 40% owned cats.
- Based on a sample of 80 women, 50% owned cats.
**Calculations:**
- The test statistic is: [ ] (to 2 decimals)
- The p-value is: [ ] (to 2 decimals)
**Conclusion:**
Based on this, we:
- Reject the null hypothesis
- Fail to reject the null hypothesis
This setup guides you through testing proportions to see if there's a significant difference between two groups at a specified significance level.
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