Assume you ran a multiple regression to gain a better understanding of the relat

Question

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 lumber sales (in $100,000s) as the response variable with housing starts (in 1,000s) and commercial construction (in 1000s) as the explanatory variables. The estimated model is Lumber Sales-Po +A Housing Starts + Commercial Constructions + . The following ANOVA table summarizes a portion of the regression results. Regression Residual Total df 2 45 47 180,770 39,375 220,145 MS 90,385 875 103.3 Coefficients Standard Errort-stat p-value Intercept Housing Starts Commercial Construction 5.37 0.76 1.25 1.71 0.09 0.33 3.14 8.44 3.78 0.003 0 0.0005 If Housing Starts were 17,000 and Commercial Construction was 3,200, the best estimate of Lumber Sales would be denomination. Make sure you convert the amounts to the appropriate thousands $22,014,000 $16,925,370 $22,290,000 $16,920,000

Explanation / Answer

Lumber sales =5.387+0.76*Housing stats+1.25*commercial construction

it is given that Housing stats =17000

commercial construction=3200

thus putting these values in the equation gives Lumber sales =5.387+0.76*Housing stats+1.25*commercial construction

=5.387+0.76*17000+1.25*3200=16925.387

Thus the correct answer is B

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