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Assume You Ran a Multiple Regression to Gain a Better

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Assume you ran a multiple regression to gain a better understanding of the relationship between lumber sales, housing starts, and commercial construction. The regression uses LumberSales (in $100,000s) as the response variable with HousingStarts (in 1,000s) and CommercialConstruction (in 1,000s) as the explanatory variables. The results of the regression are as follows: Assume you ran a multiple regression to gain a better understanding of the relationship between lumber sales, housing starts, and commercial construction. The regression uses LumberSales (in $100,000s) as the response variable with HousingStarts (in 1,000s) and CommercialConstruction (in 1,000s) as the explanatory variables. The results of the regression are as follows:   a. At the 5% significance level, are the explanatory variables jointly significant in explaining LumberSales? Explain. B) At the 5% significance level, is CommercialConstruction significant in explaining LumberSales? Explain. C) At the 5% significance level, can you conclude that the slope coefficient attached to HousingStarts differs from 1? Explain. a. At the 5% significance level, are the explanatory variables jointly significant in explaining LumberSales? Explain.
B) At the 5% significance level, is CommercialConstruction significant in explaining LumberSales? Explain.
C) At the 5% significance level, can you conclude that the slope coefficient attached to HousingStarts differs from 1? Explain.


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