Exam 13: Multiple Regression Analysis

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A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size,household income,and household neighborhood (urban,suburban,and rural).The "income" variable in this model is ____.

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A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch),production plant (Kingsland,and Yorktown),and production shift (day,and evening). In this model,"shift" is ______.

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A multiple regression analysis produced the following tables. A multiple regression analysis produced the following tables.     These results indicate that ____________. A multiple regression analysis produced the following tables.     These results indicate that ____________. These results indicate that ____________.

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A multiple regression analysis produced the following tables. A multiple regression analysis produced the following tables.     For x<sub>1</sub>= 30 and x<sub>2</sub> = 100,the predicted value of y is ____________. A multiple regression analysis produced the following tables.     For x<sub>1</sub>= 30 and x<sub>2</sub> = 100,the predicted value of y is ____________. For x1= 30 and x2 = 100,the predicted value of y is ____________.

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A multiple regression analysis produced the following tables. A multiple regression analysis produced the following tables.     The coefficient of multiple determination is ____________. A multiple regression analysis produced the following tables.     The coefficient of multiple determination is ____________. The coefficient of multiple determination is ____________.

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In the regression equation y = 1959.71 − 0.46 x1 + 2.16 x2,suppose that the you are considering the point (x1,x2)= (1.5,0.5),and furthermore,suppose that the variable x1 increases by a factor of 2 (i.e.,it doubles).What must be the change in the variable x2 so that y remains unchanged?

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A multiple regression analysis produced the following output from Excel. A multiple regression analysis produced the following output from Excel.   The correlation coefficient is ____________. The correlation coefficient is ____________.

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A multiple regression analysis produced the following tables. A multiple regression analysis produced the following tables.     The adjusted R<sup>2</sup> is ____________. A multiple regression analysis produced the following tables.     The adjusted R<sup>2</sup> is ____________. The adjusted R2 is ____________.

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The value of adjusted R2 always goes up when a nontrivial explanatory variable is added to a regression model.

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The following ANOVA table is from a multiple regression analysis. The following ANOVA table is from a multiple regression analysis.   The adjusted R<sup>2 </sup>value is __________. The adjusted R2 value is __________.

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A multiple regression analysis produced the following tables.  A multiple regression analysis produced the following tables.      Using  \alpha  = 0.10 to test the null hypothesis H<sub>0</sub>:  \beta <sub>2</sub> = 0,the critical t value is ____.  A multiple regression analysis produced the following tables.      Using  \alpha  = 0.10 to test the null hypothesis H<sub>0</sub>:  \beta <sub>2</sub> = 0,the critical t value is ____. Using α\alpha = 0.10 to test the null hypothesis H0: β\beta 2 = 0,the critical t value is ____.

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A multiple regression analysis produced the following tables.  A multiple regression analysis produced the following tables.      Using  \alpha  = 0.05 to test the null hypothesis H<sub>0</sub>:  \beta <sub>1</sub> = 0,the critical t value is ____.  A multiple regression analysis produced the following tables.      Using  \alpha  = 0.05 to test the null hypothesis H<sub>0</sub>:  \beta <sub>1</sub> = 0,the critical t value is ____. Using α\alpha = 0.05 to test the null hypothesis H0: β\beta 1 = 0,the critical t value is ____.

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The following ANOVA table is from a multiple regression analysis. The following ANOVA table is from a multiple regression analysis.   The R<sup>2 </sup>value is __________. The R2 value is __________.

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