Test the claim that the proportion of men who own cats is smaller than the proportion of women who own cats at the .05 significance level. The null and alternative hypothesis would be: Ho: PM Ho: PM MF = PF Ho: PM = PF Ho:M = PF H0: PM = PF H1: PM > PF H: PM pF H1: pM > AF H1: PM PF H1: PM
Test the claim that the proportion of men who own cats is smaller than the proportion of women who own cats at the .05 significance level. The null and alternative hypothesis would be: Ho: PM Ho: PM MF = PF Ho: PM = PF Ho:M = PF H0: PM = PF H1: PM > PF H: PM pF H1: pM > AF H1: PM PF H1: PM
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Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
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![**Title: Testing the Claim of Cat Ownership Proportions Between Men and Women**
**Introduction:**
In this exercise, we aim to test the hypothesis that the proportion of men who own cats is smaller than the proportion of women who own cats, using a significance level of 0.05.
**Hypotheses:**
The null and alternative hypotheses are formulated as follows:
- Null Hypothesis (\(H_0\)): \(p_M = p_F\), where \(p_M\) and \(p_F\) represent the proportions of men and women, respectively, who own cats.
- Alternative Hypothesis (\(H_1\)): \(p_M < p_F\)
\[
H_0: p_M = p_F
\]
\[
H_1: p_M < p_F
\]
**Types of Tests:**
- The test is specified as right-tailed, left-tailed, or two-tailed based on the alternative hypothesis. In this case, it is a left-tailed test since we are testing if \(p_M\) is less than \(p_F\).
**Data Collection:**
Based on the following sample data:
- Sample size of men (\(n_M\)): 60
- Sample proportion of men owning cats (\(p_M\)): 45%
- Sample size of women (\(n_F\)): 20
- Sample proportion of women owning cats (\(p_F\)): 55%
**Test Statistic and Critical Value:**
- Here, we need to calculate the test statistic and the critical value to make our decision. These values need to be filled in with two decimal places for accurate results.
\[
\text{Test Statistic:} \_\_\_\_
\]
\[
\text{Critical Value:} \_\_\_\_
\]
**Decision Rule:**
- Based on the calculated test statistic and critical value, determine whether to reject or fail to reject the null hypothesis.
\[
\text{Decision:}
\]
- Fail to reject the null hypothesis
- Reject the null hypothesis
**Conclusion:**
By filling out the test statistic and critical value above, we can determine whether the original claim that the proportion of men who own cats is smaller than the proportion of women who own cats holds true at the 0.05 significance level.
**Note:** This exercise involves understanding](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F3e82b789-902b-4bed-91c7-23ced64abede%2Fe1f292cf-4b05-4dd9-8a20-d03318f52b87%2F7nfsb0b_processed.jpeg&w=3840&q=75)
Transcribed Image Text:**Title: Testing the Claim of Cat Ownership Proportions Between Men and Women**
**Introduction:**
In this exercise, we aim to test the hypothesis that the proportion of men who own cats is smaller than the proportion of women who own cats, using a significance level of 0.05.
**Hypotheses:**
The null and alternative hypotheses are formulated as follows:
- Null Hypothesis (\(H_0\)): \(p_M = p_F\), where \(p_M\) and \(p_F\) represent the proportions of men and women, respectively, who own cats.
- Alternative Hypothesis (\(H_1\)): \(p_M < p_F\)
\[
H_0: p_M = p_F
\]
\[
H_1: p_M < p_F
\]
**Types of Tests:**
- The test is specified as right-tailed, left-tailed, or two-tailed based on the alternative hypothesis. In this case, it is a left-tailed test since we are testing if \(p_M\) is less than \(p_F\).
**Data Collection:**
Based on the following sample data:
- Sample size of men (\(n_M\)): 60
- Sample proportion of men owning cats (\(p_M\)): 45%
- Sample size of women (\(n_F\)): 20
- Sample proportion of women owning cats (\(p_F\)): 55%
**Test Statistic and Critical Value:**
- Here, we need to calculate the test statistic and the critical value to make our decision. These values need to be filled in with two decimal places for accurate results.
\[
\text{Test Statistic:} \_\_\_\_
\]
\[
\text{Critical Value:} \_\_\_\_
\]
**Decision Rule:**
- Based on the calculated test statistic and critical value, determine whether to reject or fail to reject the null hypothesis.
\[
\text{Decision:}
\]
- Fail to reject the null hypothesis
- Reject the null hypothesis
**Conclusion:**
By filling out the test statistic and critical value above, we can determine whether the original claim that the proportion of men who own cats is smaller than the proportion of women who own cats holds true at the 0.05 significance level.
**Note:** This exercise involves understanding
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