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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 lumber sales (in $100,000s) as the response variable with housing starts (in 1000s) (in 1,000s) and commercial construction (in 1000s) (in 1,000s) as the explanatory variables.The estimated model is Lumber Sales = β0 + β1 Housing 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 1000s) (in 1,000s) and commercial construction (in 1000s) (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.   The explanatory variables (Housing Starts and Commercial Construction) together explained approximately _____% of the variations in the response variable (Lumber Sales) . A)  18 B)  22 C)  78 D)  82 The explanatory variables (Housing Starts and Commercial Construction) together explained approximately _____% of the variations in the response variable (Lumber Sales) .


Definitions:

Mean

The average of a set of numbers, calculated by adding all the numbers together and dividing by the count of the numbers.

Sample Data

A subset of data selected from a larger population, used for statistical analysis.

Geometric Mean

The nth root of the product of n numbers, used to calculate average rates of return or growth over time.

Closing Stock Price

The final price at which a stock is traded during a trading session on a stock exchange.

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