An important factor for many purchasers of cars and trucks is the eventual resale value. A consumer organization is studying factors related to a vehicle's eventual resale value. They have collected data on the prices of SUVs, small pickups, and full-sized pickups that are resold after two years. They would like to know how the original suggested retail price of the vehicle and the type of vehicle influence the resale value.

You will use multiple linear regression to investigate this question. The dependent variable is resale value, measure by resale price as a percentage of the original price. For example, a Y value of 60 means that after two years, the price of the vehicle was 60% of its original selling price. The independent variables are the original suggested resale price (SRP) in dollars and dummy variables indicating the type of vehicle.

Question 1 1 pts Create dummy variables to indicate the type of vehicle: SUV = 1 for a sports utility vehicle, 0 otherwise; and FULLSIZE = 1 if the product was a full-sized pickup, 0 otherwise. What is the reference category that does not an associated dummy variable? [:] Full-Size Pickup C] Type of Vehicle [:] Small Pickup C] Sport Utility Question 2 1 pts Run a regression with resale as the dependent variable and suggested resale price as the independent variable. Call this Model A. What is the adjusted R-squared of this model?(two decimals) Question 3 1 pts Run a regression with resale as the dependent variable ; suggested resale price and dummy variables for SUV and FULL-SIZE PICKUP as the independent variable. Call this Model B. What is adjusted Rsquared of this model? Question 4 1 pts Based on your answers above, do you prefer Model A or Model B? O Model B Model A