Suppose that you are interested in predicting the price of a laptop computer based on its various features. The file P16_21.xlsx contains observations on the sales price and a number of potentially...

Suppose that you are interested in predicting the price of a laptop computer based on its various features. The file P16_21.xlsx contains observations on the sales price and a number of potentially relevant variables for a randomly chosen sample of laptop computers.


a. Formulate a multiple regression model that includes all potential explanatory variables and estimate it with the given sample data.

b. Interpret the estimated regression equation. Indicate the impact of each attribute on the computer’s sales price. For example, what impact does the monitor type have on the average sales price of a laptop computer?


c. How well does the estimated regression model fit the data given in the file?

d. Use the estimated regression equation to predict the price of a laptop computer with the following features: a 60-MHz processor, a battery that holds its charge for 240 minutes, 32 MB of RAM, a DX chip, a color monitor, a mouse, and a 24-hour, tollfree customer service hotline.