Confidence Intervals 15. In Problem #1, 560 of 1000 (P = 0.56) women who experienced severe morning sickness gave birth to girls. The investigators concluded there was strong evidence that women who have severe morning sickness are more likely to give birth to girls than the overall population They want to quantify the "effect size", by computing a confidence interval. a. Compute the 95% confidence interval for P = the true proportion of female babies born to women with severe morning sickness, based on these study results. b. Interpret the meaning of this 95% confidence interval in terms that could be understood by someone who has never studied statistics. c. In Problem #2, a similar study found that 179 of 320 (P = 0.56) women who experienced severe morning sickness gave birth to girls. Compute the 95% confidence interval for P = the true proportion of female babies born to women with severe morning sickness, based on these study results. d. How did changing the sample size affect the margin of error, width, and error rate of the confidence interval? Explain these changes in plain language. C. I. Margin of error: C.I. Width: C.I. Error rate: f. Compute the 99% confidence interval for P based on the study described in part c g. Compare the 99% C.I. computed for part f. with the 95% C.I. computed for part c. How does increasing the confidence level affect the margin of error, width, and error rate of the confidence interval? Explain why this is so in plain language. Margin of error: C.I. width: Error rate