# Question

Table 12.5.17 shows the results of a multiple regression analysis designed to explain the salaries of chief executive officers based on the sales of their firm and the industry group.36 The Y variable represents CEO salary (in thousands of dollars). The X1 variable is the firm’s sales (in millions of dollars). X2, X3, and X4 are indicator variables representing the industry groups aerospace, banking, and natural resources, respectively (the natural resources group includes the large oil companies). The indicator variable for the baseline group, automotive, has been omitted. There are n = 49 observations in this data set.

a. Do sales and industry groups have a significant impact on CEO salary?

b. What is the estimated effect of an additional million dollars of sales on CEO salary, adjusted for industry group?

c. Is the salary difference you estimated due to sales in part b statistically significant? What does this tell you in practical terms about salary differences?

d. According to the regression coefficient, how much more or less is the CEO of a bank paid compared to the CEO of an automotive firm of similar size?

e. Is the salary difference comparing banking to automotive that you estimated in part d statistically significant? What does this tell you in practical terms about salary differences?

a. Do sales and industry groups have a significant impact on CEO salary?

b. What is the estimated effect of an additional million dollars of sales on CEO salary, adjusted for industry group?

c. Is the salary difference you estimated due to sales in part b statistically significant? What does this tell you in practical terms about salary differences?

d. According to the regression coefficient, how much more or less is the CEO of a bank paid compared to the CEO of an automotive firm of similar size?

e. Is the salary difference comparing banking to automotive that you estimated in part d statistically significant? What does this tell you in practical terms about salary differences?

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