Now, the team is asked to develop a multiple linear regression model, with FIVE independent variables, that can best predict price of used cars. The objective is to identify a set of 5 variables (out of 16 independent variables) that yields the highest Adjusted R squared. (Hint: you need to experiment with different sets of 5 variables to find out the best performing model, with the highest adjusted R squared) 1) List the 5 independent variables in your final (best) model. 2) Report the result tables-Summary Output, F test, and t test. 3) Determine if the model is statistically significant, and comment on the fitness of the model. 4) Of 5 variables, list those that are statistically significant and those not. Interpret each coefficient of five variables in plain words