Answer :
Let's follow the steps to test the claim and constructing the appropriate confidence interval.
### a. Hypothesis Test
First, we need to establish the null and alternative hypotheses:
- Null Hypothesis [tex]\(H_0\)[/tex]: Men and women have equal success rates in challenging referee calls. Mathematically, this means: [tex]\( p_1 - p_2 = 0 \)[/tex]
- Alternative Hypothesis [tex]\(H_a\)[/tex]: Men and women do not have equal success rates in challenging referee calls. Mathematically, this means: [tex]\( p_1 - p_2 \neq 0 \)[/tex]
Given data:
- Men challenged 1416 referee calls with 426 overturned.
- Women challenged 755 referee calls with 225 overturned.
From these data, we have already calculated the following:
- Men’s success rate [tex]\( p_1 = \frac{426}{1416} = 0.301 \)[/tex]
- Women’s success rate [tex]\( p_2 = \frac{225}{755} = 0.298 \)[/tex]
Given:
- Significance level [tex]\( \alpha = 0.01 \)[/tex]
- [tex]\( P \)[/tex]-value = 0.891
#### Conclusion on Hypothesis Test:
Since the [tex]\( P \)[/tex]-value (0.891) is greater than the significance level [tex]\( \alpha = 0.01 \)[/tex]:
- We fail to reject the null hypothesis.
Thus, there is not sufficient evidence to warrant rejection of the claim that men and women have equal success in challenging calls.
### b. Confidence Interval
Next, we construct a 99% confidence interval for the difference in proportions [tex]\( \left( p_1 - p_2 \right) \)[/tex]:
The 99% confidence interval for the difference between the two proportions was calculated as:
- Lower bound: [tex]\( -0.050 \)[/tex]
- Upper bound: [tex]\( 0.056 \)[/tex]
This interval is:
[tex]\[ \left( -0.050, 0.056 \right) \][/tex]
### Final Answer for Confidence Interval:
The 99% confidence interval is [tex]\( -0.050 < (p_1 - p_2) < 0.056 \)[/tex].
### Summary
- Hypothesis Test Conclusion: We fail to reject the null hypothesis. There is not sufficient evidence to warrant rejection of the claim that men and women have equal success in challenging calls.
- 99% Confidence Interval: [tex]\( -0.050 < (p_1 - p_2) < 0.056 \)[/tex]
### a. Hypothesis Test
First, we need to establish the null and alternative hypotheses:
- Null Hypothesis [tex]\(H_0\)[/tex]: Men and women have equal success rates in challenging referee calls. Mathematically, this means: [tex]\( p_1 - p_2 = 0 \)[/tex]
- Alternative Hypothesis [tex]\(H_a\)[/tex]: Men and women do not have equal success rates in challenging referee calls. Mathematically, this means: [tex]\( p_1 - p_2 \neq 0 \)[/tex]
Given data:
- Men challenged 1416 referee calls with 426 overturned.
- Women challenged 755 referee calls with 225 overturned.
From these data, we have already calculated the following:
- Men’s success rate [tex]\( p_1 = \frac{426}{1416} = 0.301 \)[/tex]
- Women’s success rate [tex]\( p_2 = \frac{225}{755} = 0.298 \)[/tex]
Given:
- Significance level [tex]\( \alpha = 0.01 \)[/tex]
- [tex]\( P \)[/tex]-value = 0.891
#### Conclusion on Hypothesis Test:
Since the [tex]\( P \)[/tex]-value (0.891) is greater than the significance level [tex]\( \alpha = 0.01 \)[/tex]:
- We fail to reject the null hypothesis.
Thus, there is not sufficient evidence to warrant rejection of the claim that men and women have equal success in challenging calls.
### b. Confidence Interval
Next, we construct a 99% confidence interval for the difference in proportions [tex]\( \left( p_1 - p_2 \right) \)[/tex]:
The 99% confidence interval for the difference between the two proportions was calculated as:
- Lower bound: [tex]\( -0.050 \)[/tex]
- Upper bound: [tex]\( 0.056 \)[/tex]
This interval is:
[tex]\[ \left( -0.050, 0.056 \right) \][/tex]
### Final Answer for Confidence Interval:
The 99% confidence interval is [tex]\( -0.050 < (p_1 - p_2) < 0.056 \)[/tex].
### Summary
- Hypothesis Test Conclusion: We fail to reject the null hypothesis. There is not sufficient evidence to warrant rejection of the claim that men and women have equal success in challenging calls.
- 99% Confidence Interval: [tex]\( -0.050 < (p_1 - p_2) < 0.056 \)[/tex]