a. Set up the null and alternative hypotheses needed to test whether the mean earnings per share for all “target firms” differs from the mean earnings per share for all “bidder firms.” Test these hypotheses at the .10, .05, .01, and .001 levels of significance. How much evidence is there that these means differ? Explain.
b. Calculate a 95 percent confidence interval for the difference between the mean earnings per share for “target firms” and “bidder firms.” Interpret the interval.
In an article in the Journal of Retailing, Kumar, Kerwin, and Pereira study factors affecting merger and acquisition activity in retailing by comparing “target firms” and “bidder firms” with respect to several financial and marketing- related variables. If we consider two of the financial variables included in the study, suppose a random sample of 36 “target firms” gives a mean earnings per share of $ 1.52 with a standard deviation of $ 0.92, and that this sample gives a mean debt-to-equity ratio of 1.66 with a standard deviation of 0.82. Furthermore, an independent random sample of 36 “bidder firms” gives a mean earnings per share of $ 1.20 with a standard deviation of $ 0.84, and this sample gives a mean debt-to-equity ratio of 1.58 with a standard deviation of 0.81.