Two researchers conduct separate studies to test Ho: p = 0.50 against Ha: p# 0.50, each with n = 400. Researcher A gets 219 observations in the category of interest, and p = 219 / 400 =0.5475. Researcher B gets 221 in the category of interest, and p = 221 / 400 = 0.5525. Complete parts (a) through (e) below. The P-value is 0.057 (Round to three decimal places as needed.) b. Determine the P-value for Researcher B. The z test statistic is 2.10. The P-value is 0.036 (Round to three decimal places as needed.) c. Using a = 0.05, indicate in each case whether the result is "statistically significant." Interpret. The result in case A is not statistically significant. The result in case B is statistically significant. What does the statistical significance of the results above imply? O A. A difference in conclusions between two hypothesis tests always means that the test with the result that is deemed "statistically significant" is much more significant than the test with the result that is deemed "not statistically significant." O B. Hypothesis tests that produce similar P-values always have the same conclusion. O C. Hypothesis tests that result in the same conclusion do not necessarily have the same P-value. D. A difference in conclusions between two hypothesis tests does not necessarily mean that the test with the result that is deemed "statistically significant" is actually much more significant than the test with the result that is deemed "not statistically significant." d. From part a, part b, and part c, explain why important information is lost by reporting the result of a test as "P-value s 0.05" versus "P-value > 0.05," or as "reject Ho" versus "Do not reject Ho," instead of reporting the actual P-value. O A. The actual P-value is more informative because a proportion of tests equal to the significance level, a, is expected to reject the null hypothesis by chance even if it is true. O B. The actual P-value is more informative because the probability of a Type | or Type II error depends on the size of the significance level, a. O C. The actual P-value is more informative because this gives the likelihood of the results being significant. D. The actual P-value is more informative because the strength of the evidence varies based on the value. e. Find the 95% confidence interval for p for both researchers. Explain how this method shows that, in practical terms, the two studies had very similar results. The confidence interval for A is The confidence interval for B is (Round to three decimal places as needed.)