Lab 9 Today's lab will explore the sampling distribution of the sample proportion p and construct normal theory confidence intervals (CIs) for the population proportion p. This material is Sections 9.4 and 10.2 of the text. [A - B] We should find in the case (n = 100, p = .30) that the sampling distribution is approximately normal and, by experimentation, that the normal theory confidence interval p 1.96 p (1 p ) / 100 delivers nearly the advertised 95% coverage probability. [C - D] We should find that in another case (n = 100, p = .04) that the sample proportion p does not follow a bell-shaped curve. By experimentation, we should find that the normal theory confidence interval p 1.96 p (1 p ) / 100 does not deliver the advertised 95% coverage probability in this case. A. You are given a Bernoulli population (population of successes and failures) with p = .30. You are to determine the sampling distribution of the sample proportion p based on a random sample of size n = 100. Label Columns c1-c4 as x, phat, P(phat) and Cum Prob, respectively. Use Calc > Make Patterned Data > Simple Set of Numbers to enter the integers 0 (first value) through 100 (last value) in steps of 1 into Column x (store patterned data in this column). Use Calc > Calculator: store the result in Column phat, enter x/100 in the expression field. Use Calc > Probability Distributions > Binomial with 100 as number of trials and 0.30 as event probability. Check the option \"probability\