A commission on state parks is interested in identifying the factors that determine park revenues. Data are available at the state level on total revenues, acreage, number of day visitors, number of overnight visitors, and operating expenses. A portion of this data is displayed here; the entire data set is available in the file Parks.xlsx.

a. Build a linear model to predict total revenues based on the four potential explanatory variables as they are measured in the table. Evaluate the model in terms of overall goodness-of-fit. Evaluate the results for each regression parameter: Are the signs appropriate? Are the values different from zero?
b. Can you improve the model in (a) by removing or transforming one or more of the explanatory variables from the regression? If so, compare the advantages and disadvantages of the resulting regression from the one in (a).

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State Alabama Alaska Arizona Day Overnight Operating Total Acreage visitors visitors expenses revenue 4,740 1,175 703 580 6,931 683 50 3,250 3,567 46 1,721 Arkansas 51 California 1,345 64,765 Colorado 347 11,973 7,672 28,279 25,724 5,294 1,957 11,392 4,114 12,805 63,689 10,708 3,571 23,364 6,187 175,189 727 15,771 Connecticut 176 357 8,875 Delaware 17 2,795 207 8,829 5,013 Florida 454 11,302 1,189 44,738 21,606 Georgia 67 13,272 673 54,596 16,917