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Assume You Ran a Multiple Regression to Gain a Better

Question 33

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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 lumber sales (in $100,000s) as the response variable with housing starts (in 1,000s) and commercial construction (in 1,000s) as the explanatory variables. The estimated model is Lumber Sales = β0 + β1Housing Starts + β2Commercial Constructions + ε. The following ANOVA table summarizes a portion of the regression results. 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 1,000s)  as the explanatory variables. The estimated model is Lumber Sales = β<sub>0</sub> + β<sub>1</sub>Housing Starts + β<sub>2</sub>Commercial Constructions + ε. The following ANOVA table summarizes a portion of the regression results.   If Housing Starts were 17,000 and Commercial Construction was 3,200, the best estimate of Lumber Sales would be ________. A)  $16,920,000 B)  $16,925,370 C)  $22,014,000 D)  $22,290,000 If Housing Starts were 17,000 and Commercial Construction was 3,200, the best estimate of Lumber Sales would be ________.


A) $16,920,000
B) $16,925,370
C) $22,014,000
D) $22,290,000

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