Consider the ceocomp dataset of compensation information for the CEO’s of 100 U.S. companies. We wish to fit aregression model to assess the relationship between CEO compensation in thousands of dollars (includes salary andbonus, but not stock gains) and the following variates:AGE: The CEOs age, in yearsEDUCATN: The CEO’s education level (1 = no college degree; 2 = college/undergrad. degree; 3 = grad. degree)BACKGRD: Background type(1= banking/financial; 2 = sales/marketing; 3 = technical; 4 = legal; 5 = other)TENURE: Number of years employed by the firmEXPER: Number of years as the firm CEOSALES: Sales revenues, in millions of dollarsVAL: Market value of the CEO's stock, in natural logarithm unitsPCNTOWN: Percentage of firm's market value owned by the CEOPROF: Profits of the firm, before taxes, in millions of dollars1) Create a scatterplot matrix for this dataset. Briefly comment on the observed relationships between compensationand the other variates.Note that companies with negative profit do not appear to exhibit the same relationship with compensation than docompanies with positive profit (this is not surprising, as typically bonuses are only paid to the CEO when the firm showsa positive profit). Remove the firms with a negative profit from the dataset. One way this can be carried out in R is byusing the subset function. Note that this will reduce the scope of our inference to only those firms in the population witha positive profit.
Consider the ceocomp dataset of compensation information for the CEO’s of 100 U.S. companies. We wish to fit a
regression model to assess the relationship between CEO compensation in thousands of dollars (includes salary and
bonus, but not stock gains) and the following variates:
AGE: The CEOs age, in years
EDUCATN: The CEO’s education level (1 = no college degree; 2 = college/undergrad. degree; 3 = grad. degree)
BACKGRD: Background type(1= banking/financial; 2 = sales/marketing; 3 = technical; 4 = legal; 5 = other)
TENURE: Number of years employed by the firm
EXPER: Number of years as the firm CEO
SALES: Sales revenues, in millions of dollars
VAL: Market value of the CEO's stock, in natural logarithm units
PCNTOWN: Percentage of firm's market value owned by the CEO
PROF: Profits of the firm, before taxes, in millions of dollars
1) Create a scatterplot matrix for this dataset. Briefly comment on the observed relationships between compensation
and the other variates.
Note that companies with negative profit do not appear to exhibit the same relationship with compensation than do
companies with positive profit (this is not surprising, as typically bonuses are only paid to the CEO when the firm shows
a positive profit). Remove the firms with a negative profit from the dataset. One way this can be carried out in R is by
using the subset function. Note that this will reduce the scope of our inference to only those firms in the population with
a positive profit.
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