Suppose you are interested in predicting the price of a laptop computer based on its features. The file P13_35.XLS contains observations on the sales price and a number of potentially relevant variables for a randomly chosen sample of laptop computers. 

a. Estimate a multiple regression model that predicts the price of a laptop computer using the following quantitative variables: the speed of the computer’s CPU, the length of time the computer’s battery maintains its charge, and the size of the computer’s RAM. Assess this set of explanatory variables with an F test, and report a p-value. 

b. Do explanatory variables that model the computer’s chip type and monitor type contribute significantly to the prediction of the laptop’s sales price? Let the equation estimated in part a serve as the reduced equation in a partial F test. Employ a 5% significance level in conducting the appropriate hypothesis test in this case. 

c. Do explanatory variables that model the computer’s pointing device and the availability of a help line for buyers contribute significantly to the prediction of the laptop’s sales price? Let the most appropriate equation found from the analysis in part b serve as the reduced equation in a partial F test. Again, employ a 5% significance level in conducting the appropriate hypothesis test in this case.