Using the z-distribution, as we are working with a proportion, it is found that:
A. The 98% confidence interval is (-0.082, 0.141), and it means that we are 98% sure that the true difference of the population proportions are in this interval.
B. Since 0 is part of the confidence interval, it does not give convincing evidence of a difference between the population proportions.
For each sample, they are given by:
[tex]p_F = \frac{53}{150} = 0.3533, s_F = \sqrt{\frac{0.3533(0.6467)}{150}} = 0.039[/tex]
[tex]p_M = \frac{89}{275} = 0.3236, s_M = \sqrt{\frac{0.3236(0.6764)}{275}} = 0.0282[/tex]
Hence, for the distribution of differences:
[tex]p = p_F - p_M = 0.3533 - 0.3236 = 0.0297[/tex]
[tex]s = \sqrt{s_F^2 + s_M^2} = \sqrt{0.039^2 + 0.0282^2} = 0.048[/tex]
It is given by:
[tex]p \pm zs[/tex]
98% confidence interval, hence, using a z-distribution calculator, the critical value is of z = 2.327.
Then:
[tex]p - zs = 0.0297 - 2.327(0.048) = -0.082[/tex]
[tex]p + zs = 0.0297 + 2.327(0.048) = 0.141[/tex]
The 98% confidence interval is (-0.082, 0.141), and it means that we are 98% sure that the true difference of the population proportions are in this interval.
Item b:
Since 0 is part of the confidence interval, it does not give convincing evidence of a difference between the population proportions.
To learn more about the z-distribution, you can check https://brainly.com/question/25890103