The le highway.csv contains information about 39 sections of large highways in the state of Minnesota in 1973. The goal of the analysis is to understand the impact of design variables on the automobile accident rate. Hereunder is a table of all the variables in the data set (all logarithms have base e).

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5. The file highway . cav contains information about 39 sections of large highways in the state of Minnesota in 1973. The goal of the analysis is to understand the impact of design variables on the automobile accident rate. Hereunder is a table of all the variables in the data set (all logarithms have base e). Variable Description logRate Logarithm of 1973 accident rate per million vehicle miles logLen Logarithm of the length of the segment in miles logADT Logarithm of average daily traffic count in thousands log Trks Logarithm of truck volume as a percent of the total volume Slim 1973 speed limit Lwid Lane width in feet Shld Out shoulder width in feet on the roadway Itg Number of freeway-type interchanges per mile in the segment logSigs1 Logarithm of (1 + number of signaled interchanges per mile) Acpt Number of access points per mile in the segment (a) Use forward selection with F-test to construct a regression model with logRate as the response. Set the significance level at 0.05, and restrict the attention only to linear terms, i.e., no higher order polynomial or interaction terms. (b) Perform an all subsets model selection using the Cp criterion. Report the predictors in the best model. (Hint: You need to specify the nvmax argument in the regsubsets function.) (c) Is there heteroscedasticity and/or non-linearity in the model obtained from part (b)? If so, fix it/them