Homework Help is Here – Start Your Trial Now!
Math
Statistics
Listed in the table below are the selling prices, number of bedrooms, number of full baths, and above-ground square footage for 15 single-family residential homes that sold in Boulder, CO in January of 2011. Above-Ground Sq.Ft. Sale Price # Bedrooms# Full baths $479,500 3 1 $394,100 3 1 $638,000 3 2 $745,900 4 2 4521 $300,000 3 1 950 $1,366,600 5 3 3536 $587,500 5 2 1204 $399,000 3 1 1070 $1,450,000 5 2 5308 $275,200 2 1 745 $298,500 3 1 1026 $1,269,000 3 3 2598 $490,000 3 2 1026 $1,700,000 5 4 3774 $310,000 2 2 1760 Assuming the regression assumptions are met, perform the multiple regression of y = sale price on the set of predictor variables x₁ = number of bedrooms, x2 = number of full bath and x3 = above-ground square footage. Conduct the F test for the significance of overall regression and state your conclusion. Use a significance level of a = 0.05. 1222 1128 1204 Select one: O a. Since the p-value is approximately 0, there is evidence that a linear relationship exists between sale price and each of the predictor variables. O b. Since the p-value is approximately 0, there is evidence that a linear relationship exists between sale price and at least one of the predictor variables. O c. Since the p-value is greater than 0.05, there is evidence that a linear relationship does not exist between sale price and the set of predictor variables. O d. Since the p-value is greater than 0.05, this multiple regression is not significant. Individual t tests must be performed to determine whether a linear relationship exists between sale price and the individual predictors.

Listed in the table below are the selling prices, number of bedrooms, number of full baths, and above-ground square footage for 15 single-family residential homes that sold in Boulder, CO in January of 2011. Above-Ground Sq.Ft. Sale Price # Bedrooms# Full baths $479,500 3 1 $394,100 3 1 $638,000 3 2 $745,900 4 2 4521 $300,000 3 1 950 $1,366,600 5 3 3536 $587,500 5 2 1204 $399,000 3 1 1070 $1,450,000 5 2 5308 $275,200 2 1 745 $298,500 3 1 1026 $1,269,000 3 3 2598 $490,000 3 2 1026 $1,700,000 5 4 3774 $310,000 2 2 1760 Assuming the regression assumptions are met, perform the multiple regression of y = sale price on the set of predictor variables x₁ = number of bedrooms, x2 = number of full bath and x3 = above-ground square footage. Conduct the F test for the significance of overall regression and state your conclusion. Use a significance level of a = 0.05. 1222 1128 1204 Select one: O a. Since the p-value is approximately 0, there is evidence that a linear relationship exists between sale price and each of the predictor variables. O b. Since the p-value is approximately 0, there is evidence that a linear relationship exists between sale price and at least one of the predictor variables. O c. Since the p-value is greater than 0.05, there is evidence that a linear relationship does not exist between sale price and the set of predictor variables. O d. Since the p-value is greater than 0.05, this multiple regression is not significant. Individual t tests must be performed to determine whether a linear relationship exists between sale price and the individual predictors.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
See similar textbooks
icon
Related questions
Question
Listed in the table below are the selling prices, number of bedrooms, number of full baths, and above-ground square footage for 15 single-family residential homes that sold in Boulder, CO in January of 2011. 4 Sale Price # Bedrooms# Full baths $479,500 3 $394,100 3 $638,000 3 $745,900 $300,000 $1,366,600 $587,500 5 $399,000 3 $1,450,000 5 $275,200 2 $298,500 3 3 $1,269,000 $490,000 3 1026 4 3774 $1,700,000 5 2 $310,000 2 1760 Assuming the regression assumptions are met, perform the multiple regression of y = sale price on the set of predictor variables x₁ = number of bedrooms, x2 = number of full baths and x3 = above-ground square footage. Conduct the F test for the significance of overall regression and state your conclusion. Use a significance level of a = 0.05. 3 LO 5 1 1 2 2 1 3 2 1 2 1 1 3 Above-Ground Sq.Ft. 2 1222 1128 1204 4521 950 3536 1204 1070 5308 745 1026 2598 Select one: a. Since the p-value is approximately 0, there is evidence that a linear relationship exists between sale price and each of the predictor variables. O b. Since the p-value is approximately 0, there is evidence that a linear relationship exists between sale price and at least one of the predictor variables. O c. Since the p-value is greater than 0.05, there is evidence that a linear relationship does not exist between sale price and the set of predictor variables. O d. Since the p-value is greater than 0.05, this multiple regression is not significant. Individual t tests must be performed to determine whether a linear relationship exists between sale price and the individual predictors.
Transcribed Image Text:Listed in the table below are the selling prices, number of bedrooms, number of full baths, and above-ground square footage for 15 single-family residential homes that sold in Boulder, CO in January of 2011. 4 Sale Price # Bedrooms# Full baths $479,500 3 $394,100 3 $638,000 3 $745,900 $300,000 $1,366,600 $587,500 5 $399,000 3 $1,450,000 5 $275,200 2 $298,500 3 3 $1,269,000 $490,000 3 1026 4 3774 $1,700,000 5 2 $310,000 2 1760 Assuming the regression assumptions are met, perform the multiple regression of y = sale price on the set of predictor variables x₁ = number of bedrooms, x2 = number of full baths and x3 = above-ground square footage. Conduct the F test for the significance of overall regression and state your conclusion. Use a significance level of a = 0.05. 3 LO 5 1 1 2 2 1 3 2 1 2 1 1 3 Above-Ground Sq.Ft. 2 1222 1128 1204 4521 950 3536 1204 1070 5308 745 1026 2598 Select one: a. Since the p-value is approximately 0, there is evidence that a linear relationship exists between sale price and each of the predictor variables. O b. Since the p-value is approximately 0, there is evidence that a linear relationship exists between sale price and at least one of the predictor variables. O c. Since the p-value is greater than 0.05, there is evidence that a linear relationship does not exist between sale price and the set of predictor variables. O d. Since the p-value is greater than 0.05, this multiple regression is not significant. Individual t tests must be performed to determine whether a linear relationship exists between sale price and the individual predictors.
Expert Solution
steps

Step by step

Solved in 5 steps with 3 images

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman
SEE MORE TEXTBOOKS