2. Use R/Stata to estimate the following four models. Round the coefficients to the nearest whole number. (Attach the R/Stata output to the answer sheet.) (a) Model 1: Price = Bo + BiSaft (b) Model 2: Price = Bo + BISaft + B2Baths (c) Model 3: Price = Bo + B1Beds + B2Baths (d) Model 4: Price = Bo + BISaft + B2Beds + B3Baths 3. For Model 4 in (d) above, interpret the coefficients for SqFt, Bed, and Bath.\f4. (a) Fill in the table below with the Standard Error of the estimate and Adjusted R given by R/Stata for each model. (Attach the R/Stata output to the answer sheet.) Standard Error Adjusted R2 Model 1 Model 2 Model 3 Model 4 (b) Based on you answer in (a) determine the best model for predicting Price. Explain briefly.5. Use each model to estimate the price of a 2000 square foot house with 3 bedrooms and 2 bathrooms. (a) Model 1 (b) Model 4 6. For the multiple regression model determine which variables are individually significant in predicting Price at the 5% significance level. Explain you answers briefly. (a) Model 3 (b) Model 47. For each multiple regression model, conduct a test of joint significance at the 5% significance level to determine if the variables are jointly significant predictors of Price. Explain your answers briefly. (a) Model 2 (b) Model 3