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Using data on 500 homes listed for sale to estimate the significant predictors of the listing price ( $1000's), information on house size (sqft in 100's), age, number of beds, number of bathrooms, and garage size (in number of cars) are collected. The following is the estimated regression model: PRICE = B1 + B2 AGE+ B3 BEDROOMS+ B,BATHROOMS+ Bs SQFT +e %3D Following least squares regression, the residuals are saved (using variable name EHAT). An auxiliary regression model was developed using the squared residuals as a dependent variable and all the independent variables in the above model. The purpose of the auxiliary regression model is to test for the presence of heteroskedasticity in the price model. Suppose the R-squared of the auxiliary regression model is 0.3028. a. The null hypothesis of the Breusch-Pagan test for heteroskedasticity is ( Select] b. Compute the Breusch-Pagan test statistic: Y- ( Select] c. The degrees of freedom for the chi-squared distribution for this test is [ Select ]

Using data on 500 homes listed for sale to estimate the significant predictors of the listing price ( $1000's), information on house size (sqft in 100's), age, number of beds, number of bathrooms, and garage size (in number of cars) are collected. The following is the estimated regression model: PRICE = B1 + B2 AGE+ B3 BEDROOMS+ B,BATHROOMS+ Bs SQFT +e %3D Following least squares regression, the residuals are saved (using variable name EHAT). An auxiliary regression model was developed using the squared residuals as a dependent variable and all the independent variables in the above model. The purpose of the auxiliary regression model is to test for the presence of heteroskedasticity in the price model. Suppose the R-squared of the auxiliary regression model is 0.3028. a. The null hypothesis of the Breusch-Pagan test for heteroskedasticity is ( Select] b. Compute the Breusch-Pagan test statistic: Y- ( Select] c. The degrees of freedom for the chi-squared distribution for this test is [ Select ]

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
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Using data on 500 homes listed for sale to estimate the significant predictors of the listing price ( $1000's), information on house size (sqft in 100's), age, number of beds, number of bathrooms, and garage size (in number of cars) are collected. The following is the estimated regression model: PRICE = B1 + B2 AGE+ B3 BEDROOMS+ B,BATH ROOMS+ B, SQFT+e %3D Following least squares regression, the residuals are saved (using variable name EHAT). An auxiliary regression model was developed using the squared residuals as a dependent variable and all the independent variables in the above model. The purpose of the auxiliary regression model is to test for the presence of heteroskedasticity in the price model. Suppose the R-squared of the auxiliary regression model is 0.3028. a. The null hypothesis of the Breusch-Pagan test for heteroskedasticity is ( Select] b. Compute the Breusch-Pagan test statistic: y2= [Select] c. The degrees of freedom for the chi-squared distribution for this test is [ Select ] d. Based on the chi-squared test static, the p-value = (Select ] V (use the pchisq() function in R) e. Conclusion: (Select) Reject the null hypothesis. Therefore the error variance is constant.
Transcribed Image Text:Using data on 500 homes listed for sale to estimate the significant predictors of the listing price ( $1000's), information on house size (sqft in 100's), age, number of beds, number of bathrooms, and garage size (in number of cars) are collected. The following is the estimated regression model: PRICE = B1 + B2 AGE+ B3 BEDROOMS+ B,BATH ROOMS+ B, SQFT+e %3D Following least squares regression, the residuals are saved (using variable name EHAT). An auxiliary regression model was developed using the squared residuals as a dependent variable and all the independent variables in the above model. The purpose of the auxiliary regression model is to test for the presence of heteroskedasticity in the price model. Suppose the R-squared of the auxiliary regression model is 0.3028. a. The null hypothesis of the Breusch-Pagan test for heteroskedasticity is ( Select] b. Compute the Breusch-Pagan test statistic: y2= [Select] c. The degrees of freedom for the chi-squared distribution for this test is [ Select ] d. Based on the chi-squared test static, the p-value = (Select ] V (use the pchisq() function in R) e. Conclusion: (Select) Reject the null hypothesis. Therefore the error variance is constant.
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