A sample consists of 500 houses sold in Karachi between January 2020 and December 2020. The multiple linear regression analysis is carried out to predict the house prices for investment in residential properties in Karachi, Pakistan. The output below is produced using SPSS. (300 words) Table: Coefficients ModelUnstandardizedCoefficients t VIFConstant14.2085.736 Age of house-0.299-2.3221.58Square footage of the house0.3642.9311.71Income of families in the area0.0040.3921.01Transportation time to major markets-0.337-2.6191.90R2 = 0.67; DW = 2.08 Dependent Variable: House price (Pakistani rupees in Million)You are required to write the multiple regressionHow would you interpret the above ‘Output’ of a regression analysis performed in SPSS?From the above results, what can you say about the nature of autocorrelation?Is there multicollinearity in regression? How do you know?

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Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

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A sample consists of 500 houses sold in Karachi between January 2020 and December 2020. The multiple linear regression analysis is carried out to predict the house prices for investment in residential properties in Karachi, Pakistan. The output below is produced using SPSS. (300 words) Table: Coefficients

Model	Unstandardized Coefficients	t	VIF
Constant	14.208	5.736
Age of house	-0.299	-2.322	1.58
Square footage of the house	0.364	2.931	1.71
Income of families in the area	0.004	0.392	1.01
Transportation time to major markets	-0.337	-2.619	1.90
R² = 0.67; DW = 2.08

Dependent Variable: House price (Pakistani rupees in Million)

You are required to write the multiple regression
How would you interpret the above ‘Output’ of a regression analysis performed in SPSS?
From the above results, what can you say about the nature of autocorrelation?
Is there multicollinearity in regression? How do you know?

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