R STUDIO CODES NEEDED i need answers for each question. please provide r codes where needed

data set looks something like this, make a dummy data set like the one in the picture

let the dummy set be called- data

a)Produce the pairwise correlations and scatterplot matrix for all pairs of quantitative variables in the data. Describe how each quantitative predictor for sale price rank, in terms their correlation coeficient, from highest to lowest.

(b) Based on the scatterplot matrix, for which single predictor of sale price would the assumption of constant variance be strongly violated? Confirm your answer by showing an appropriate plot of the (standardized) residuals.

show how to get standardized residuals and how to find a predictor

c) Fit an additive linear regression model with all available predictors variables for sale price. List the estimated regression coeficients and the p-values for the corresponding t-tests for these coef- cients. Interpret the estimated model coeficient if the t-test result was signicant.(tell me how to know if it is significant)

d)Start with the full model (`fullmodel') fitted in part c) above and use backward elimination with AIC. What is the final model (write the fitted model)? then use BIC instead of AIC and repeat(what is the final model?) Here are some R codes you may use for parts d) # backward AIC step(fullmodel, direction = "backward") # backward BIC; n is the number of data points step(fullmodel, direction = "backward", k=log(n))

e) Using a 2-by-2 layout, show the 4 diagnostic plots that are obtained in R by plotting the model obtained in part d)

ID sale list bedroom bathroom parking maxsqfoot taxes lotwidth 95 679900 2 2 1 2577.000 672000 755000 NA NA 17.00 19.00 lotlength location 120.00 T 15.65 T 118.00 T 1 2 NA 61 44 790000 649000 799900 819000 3 3 5 2000 1500 49.00 31.99 174 816000 3 3 4 109.91 M 109.91 M 205 816000 819900 3 3 1500 31.99 179 820000 828800 3 3 3 2000 26.90 132 3 2 25.00 1500 NA 850000 849000 850000 173 3160.000 4800.000 4200.000 4200.000 4181.000 3917.000 4413.000 3917.000 3558.000 3676.000 6000.000 3150.000 113.29 M 100.00 M 103.75 M 100.00 M 3 837000 837000 837000 855000 860000 2 41.15 MN mm 185 2 1500 25.00 110 699000 6 3 NA 119.60 T 25.00 16.10 81 1 2 2 NA NA 43.69 T 868900 875000 172 862000 3 2 6 NA 41.99 162.54 M 76 875000 895000 2 2 NA NA 18.00 69.25 T 120.00 T 83 3 1 NA 26.00 890000 905000 900000 918000 175 3 3 4 NA 9.76 M 4217.000 4506.000 4716.000 5546.000 49.72 65.10 164 3 3 NA 171 920000 930000 930000 920000 939000 930000 4 2000 41.12 101.00 M 109.91 M 109.91 M 204 4 4 2000 41.12 5546.000 5219.000 155 940000 899900 3 2 s 5 NA 49.67 120.00 M 152 879800 4 2 5 NA 4834.000 52.00 M 955000 968000 117.00 40.03 180 899000 3 2 NA 4819.000 95.78 M 162 om MA ANN 10 11 ID sale list bedroom bathroom parking maxsqfoot taxes lotwidth 95 679900 2 2 1 2577.000 672000 755000 NA NA 17.00 19.00 lotlength location 120.00 T 15.65 T 118.00 T 1 2 NA 61 44 790000 649000 799900 819000 3 3 5 2000 1500 49.00 31.99 174 816000 3 3 4 109.91 M 109.91 M 205 816000 819900 3 3 1500 31.99 179 820000 828800 3 3 3 2000 26.90 132 3 2 25.00 1500 NA 850000 849000 850000 173 3160.000 4800.000 4200.000 4200.000 4181.000 3917.000 4413.000 3917.000 3558.000 3676.000 6000.000 3150.000 113.29 M 100.00 M 103.75 M 100.00 M 3 837000 837000 837000 855000 860000 2 41.15 MN mm 185 2 1500 25.00 110 699000 6 3 NA 119.60 T 25.00 16.10 81 1 2 2 NA NA 43.69 T 868900 875000 172 862000 3 2 6 NA 41.99 162.54 M 76 875000 895000 2 2 NA NA 18.00 69.25 T 120.00 T 83 3 1 NA 26.00 890000 905000 900000 918000 175 3 3 4 NA 9.76 M 4217.000 4506.000 4716.000 5546.000 49.72 65.10 164 3 3 NA 171 920000 930000 930000 920000 939000 930000 4 2000 41.12 101.00 M 109.91 M 109.91 M 204 4 4 2000 41.12 5546.000 5219.000 155 940000 899900 3 2 s 5 NA 49.67 120.00 M 152 879800 4 2 5 NA 4834.000 52.00 M 955000 968000 117.00 40.03 180 899000 3 2 NA 4819.000 95.78 M 162 om MA ANN 10 11