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.

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.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question

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.

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Expert Solution

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Given information:

$\begin{array}{rcl} Intercept & = & 422.7157 \\ S . E_{I n t e r c e p t} & = & 0.27444 \\ Slope & = & 1.5475 \\ S . E_{S l o p e} & = & 1.02212 \\ D . F & = & 182 \end{array}$

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