Part B Research Question: Is there a relation between SalePrice and BuildingArea? The output below relates to the relation betweenSalePrice and BuildingArea.   >results2 <-lm (SalePrice  ~ BuildingArea)  >results2 Call: lm(formula = SalePrice  ~ BuildingArea) Coefficients: (Intercept)      BuildingArea   422.71568         1.5475 >summary(results2)Call: lm(formula = SalePrice  ~ BuildingArea) Coefficients:                Estimate Std. Error t value   Pr(>|t|)    (Intercept)     422.71568    0.27444   82.77   <2e-16 BuildingArea     1.54750     1.02212   1.514     0.598 Residual standard error: 1.706 on 182 degrees of freedomMultiple R-squared:  0.7251,    Adjusted R-squared:  0.5245 F-statistic: 612.4 on 1 and 182 DF,     p-value: < 2.2e-16>confint(results2)                      2.5 %         97.5 % BuildingArea   -125.49        128.58     (1). Provide a 95% confidence interval for the population slope of the regression line.    -What is the lower bound of the 95% confidence interval? (4 decimal places) =   -What is the upper bound of the 95%  confidence interval? (4 decimal places) =   Q)Based on this confidence interval you provided in part (1), is there a significant linear relation between PS and BA? (Choose one from below)    -Yes, the null value (zero) lies outside this C.I. Hence there could be no linear relation between SP and BA. -No, the null value (zero) lies outside this C.I. Hence there could be a linear relation between SP and BA. -No, the null value (zero) lies inside this C.I. Hence there could be no linear relation between SP and BA. -Yes, the null value (zero) lies inside this C.I. Hence there could be no linear relation between SP and BA.       What is the R2 value for the relationship between  SP and LS? Use the output from Question 3 Part A.(give your answer in decimals and for 2 decimal places) =     What is the R2 value for the relationship between  SP and BA? (give your answer in decimals and for 4 decimal places)   =     Q) Which of the 2 predictors, LS or BA, is a better predictor of SP? (Choose one from below)    -LS, because P value for the LS predictor is larger than the BA predictor. -LS, because the R2 for the LS predictor is lower and we don't reject the H0:β =0. -BA, because the R2 for the BA predictor is larger and we don't reject the H0:β =0. -LS, because the R2 for the LS predictor is larger and we reject the H0:β =0. -BA, because the R2 for the BA predictor is larger and we reject the H0:β =0.