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Exhibit 15-1 In a regression model involving 44 observations,the following estimated regression equation was obtained. Exhibit 15-1 In a regression model involving 44 observations,the following estimated regression equation was obtained.   For this model SSR = 600 and SSE = 400. -Refer to Exhibit 15-1.The computed F statistics for testing the significance of the above model is A) 1.500 B) 20.00 C) 0.600 D) 0.6667 For this model SSR = 600 and SSE = 400. -Refer to Exhibit 15-1.The computed F statistics for testing the significance of the above model is


A) 1.500
B) 20.00
C) 0.600
D) 0.6667

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Exhibit 15-8 The following estimated regression model was developed relating yearly income (Y in $1,000s) of 30 individuals with their age (X1) and their gender (X2) (0 if male and 1 if female) . Exhibit 15-8 The following estimated regression model was developed relating yearly income (Y in $1,000s) of 30 individuals with their age (X<sub>1</sub>) and their gender (X<sub>2</sub>) (0 if male and 1 if female) .   Also provided are SST = 1,200 and SSE = 384. -Refer to Exhibit 15-8.The multiple coefficient of determination is A) 0.32 B) 0.42 C) 0.68 D) 0.50 Also provided are SST = 1,200 and SSE = 384. -Refer to Exhibit 15-8.The multiple coefficient of determination is


A) 0.32
B) 0.42
C) 0.68
D) 0.50

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A regression was performed on a sample of 20 observations.Two independent variables were included in the analysis,X and Z.The relationship between X and Z is Z = X2.The following estimated equation was obtained. A regression was performed on a sample of 20 observations.Two independent variables were included in the analysis,X and Z.The relationship between X and Z is Z = X<sup>2</sup>.The following estimated equation was obtained.    The standard errors for the coefficients are S<sub>b1</sub> = 4.85 and S<sub>b2</sub> = 0.21 For this model,SSR = 520.2 and SSE = 340.6  a.Estimate the value of Y when X = 5. b.Compute the appropriate t ratios. c.Test for the significance of the coefficients at the 5% level.Which variable(s)is (are)significant? d.Compute the coefficient of determination and the adjusted coefficient of determination.Interpret the meaning of the coefficient of determination. e.Test the significance of the relationship among the variables at the 5% level of significance. The standard errors for the coefficients are Sb1 = 4.85 and Sb2 = 0.21 For this model,SSR = 520.2 and SSE = 340.6 a.Estimate the value of Y when X = 5. b.Compute the appropriate t ratios. c.Test for the significance of the coefficients at the 5% level.Which variable(s)is (are)significant? d.Compute the coefficient of determination and the adjusted coefficient of determination.Interpret the meaning of the coefficient of determination. e.Test the significance of the relationship among the variables at the 5% level of significance.

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a.106.72
b.2.6,3.8
c.For x,t = 2.6;p-val...

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The multiple coefficient of determination is


A) MSR/MST
B) MSR/MSE
C) SSR/SST
D) SSE/SSR

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Exhibit 15-2 A regression model between sales (Y in $1,000) ,unit price (X1 in dollars) and television advertisement (X2 in dollars) resulted in the following function: Exhibit 15-2 A regression model between sales (Y in $1,000) ,unit price (X<sub>1</sub> in dollars) and television advertisement (X<sub>2</sub> in dollars) resulted in the following function:   For this model SSR = 3500,SSE = 1500,and the sample size is 18. -Refer to Exhibit 15-2.The multiple coefficient of correlation for this problem is A) 0.70 B) 0.8367 C) 0.49 D) 0.2289 For this model SSR = 3500,SSE = 1500,and the sample size is 18. -Refer to Exhibit 15-2.The multiple coefficient of correlation for this problem is


A) 0.70
B) 0.8367
C) 0.49
D) 0.2289

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A regression model involving 8 independent variables for a sample of 69 periods resulted in the following sum of squares.  A regression model involving 8 independent variables for a sample of 69 periods resulted in the following sum of squares.     a.Compute the coefficient of determination. b.At  \alpha  = 0.05,test to determine whether or not the model is significant. a.Compute the coefficient of determination. b.At α\alpha = 0.05,test to determine whether or not the model is significant.

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a.0.83
b.F = 36.62;p...

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Exhibit 15-2 A regression model between sales (Y in $1,000) ,unit price (X1 in dollars) and television advertisement (X2 in dollars) resulted in the following function: Exhibit 15-2 A regression model between sales (Y in $1,000) ,unit price (X<sub>1</sub> in dollars) and television advertisement (X<sub>2</sub> in dollars) resulted in the following function:   For this model SSR = 3500,SSE = 1500,and the sample size is 18. -Refer to Exhibit 15-2.The coefficient of the unit price indicates that if the unit price is A) increased by $1 (holding advertising constant) ,sales are expected to increase by $3 B) decreased by $1 (holding advertising constant) ,sales are expected to decrease by $3 C) increased by $1 (holding advertising constant) ,sales are expected to increase by $4,000 D) increased by $1 (holding advertising constant) ,sales are expected to decrease by $3,000 For this model SSR = 3500,SSE = 1500,and the sample size is 18. -Refer to Exhibit 15-2.The coefficient of the unit price indicates that if the unit price is


A) increased by $1 (holding advertising constant) ,sales are expected to increase by $3
B) decreased by $1 (holding advertising constant) ,sales are expected to decrease by $3
C) increased by $1 (holding advertising constant) ,sales are expected to increase by $4,000
D) increased by $1 (holding advertising constant) ,sales are expected to decrease by $3,000

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Exhibit 15-6 Below you are given a partial computer output based on a sample of 16 observations. Exhibit 15-6 Below you are given a partial computer output based on a sample of 16 observations.    -Refer to Exhibit 15-6.The test statistic used to determine if there is a relationship among the variables equals A) -1.4 B) 0.2 C) 0.77 D) 5 -Refer to Exhibit 15-6.The test statistic used to determine if there is a relationship among the variables equals


A) -1.4
B) 0.2
C) 0.77
D) 5

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Exhibit 15-8 The following estimated regression model was developed relating yearly income (Y in $1,000s) of 30 individuals with their age (X1) and their gender (X2) (0 if male and 1 if female) . Exhibit 15-8 The following estimated regression model was developed relating yearly income (Y in $1,000s) of 30 individuals with their age (X<sub>1</sub>) and their gender (X<sub>2</sub>) (0 if male and 1 if female) .   Also provided are SST = 1,200 and SSE = 384. -Refer to Exhibit 15-8.The model A) is significant B) is not significant C) would be significant is the sample size was larger than 30 D) None of these alternatives is correct. Also provided are SST = 1,200 and SSE = 384. -Refer to Exhibit 15-8.The model


A) is significant
B) is not significant
C) would be significant is the sample size was larger than 30
D) None of these alternatives is correct.

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The estimate of the multiple regression equation based on the sample data,which has the form of E(y) = The estimate of the multiple regression equation based on the sample data,which has the form of E(y) =   Is A) a simple linear regression model B) a multiple nonlinear regression model C) an estimated multiple regression equation D) a multiple regression equation Is


A) a simple linear regression model
B) a multiple nonlinear regression model
C) an estimated multiple regression equation
D) a multiple regression equation

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In a multiple regression model,the error term ε\varepsilon is assumed to be a random variable with a mean of


A) zero
B) -1
C) 1
D) any value

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The adjusted multiple coefficient of determination is adjusted for


A) the number of dependent variables
B) the number of independent variables
C) the number of equations
D) detrimental situations

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The following regression model has been proposed to predict monthly sales at a shoe store. The following regression model has been proposed to predict monthly sales at a shoe store.    a.Predict sales (in dollars)for the shoe store if the competitor's previous month's sales were $9,000,the store's previous month's sales were $30,000,and no radio advertisements were run. b.Predict sales (in dollars)for the shoe store if the competitor's previous month's sales were $9,000,the store's previous month's sales were $30,000,and 10 radio advertisements were run. a.Predict sales (in dollars)for the shoe store if the competitor's previous month's sales were $9,000,the store's previous month's sales were $30,000,and no radio advertisements were run. b.Predict sales (in dollars)for the shoe store if the competitor's previous month's sales were $9,000,the store's previous month's sales were $30,000,and 10 radio advertisements were run.

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a.$373,000...

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Exhibit 15-8 The following estimated regression model was developed relating yearly income (Y in $1,000s) of 30 individuals with their age (X1) and their gender (X2) (0 if male and 1 if female) . Exhibit 15-8 The following estimated regression model was developed relating yearly income (Y in $1,000s) of 30 individuals with their age (X<sub>1</sub>) and their gender (X<sub>2</sub>) (0 if male and 1 if female) .   Also provided are SST = 1,200 and SSE = 384. -Refer to Exhibit 15-8.The test statistic for testing the significance of the model is A) 0.73 B) 1.47 C) 28.69 D) 5.22 Also provided are SST = 1,200 and SSE = 384. -Refer to Exhibit 15-8.The test statistic for testing the significance of the model is


A) 0.73
B) 1.47
C) 28.69
D) 5.22

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Exhibit 15-1 In a regression model involving 44 observations,the following estimated regression equation was obtained. Exhibit 15-1 In a regression model involving 44 observations,the following estimated regression equation was obtained.   For this model SSR = 600 and SSE = 400. -Refer to Exhibit 15-1.The coefficient of determination for the above model is A) 0.667 B) 0.600 C) 0.336 D) o.400 For this model SSR = 600 and SSE = 400. -Refer to Exhibit 15-1.The coefficient of determination for the above model is


A) 0.667
B) 0.600
C) 0.336
D) o.400

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Exhibit 15-4 a. Exhibit 15-4 a.   b.   c.   d.   -Which equation describes the multiple regression equation? A) Equation A B) Equation B C) Equation C D) Equation D b. Exhibit 15-4 a.   b.   c.   d.   -Which equation describes the multiple regression equation? A) Equation A B) Equation B C) Equation C D) Equation D c. Exhibit 15-4 a.   b.   c.   d.   -Which equation describes the multiple regression equation? A) Equation A B) Equation B C) Equation C D) Equation D d. Exhibit 15-4 a.   b.   c.   d.   -Which equation describes the multiple regression equation? A) Equation A B) Equation B C) Equation C D) Equation D -Which equation describes the multiple regression equation?


A) Equation A
B) Equation B
C) Equation C
D) Equation D

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A variable that takes on the values of 0 or 1 and is used to incorporate the effect of qualitative variables in a regression model is called


A) an interaction
B) a constant variable
C) a dummy variable
D) None of these alternatives is correct.

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In a multiple regression analysis involving 10 independent variables and 81 observations,SST = 120 and SSE = 42.The coefficient of determination is


A) 0.81
B) 0.11
C) 0.35
D) 0.65

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Exhibit 15-8 The following estimated regression model was developed relating yearly income (Y in $1,000s) of 30 individuals with their age (X1) and their gender (X2) (0 if male and 1 if female) . Exhibit 15-8 The following estimated regression model was developed relating yearly income (Y in $1,000s) of 30 individuals with their age (X<sub>1</sub>) and their gender (X<sub>2</sub>) (0 if male and 1 if female) .   Also provided are SST = 1,200 and SSE = 384. -Refer to Exhibit 15-8.The yearly income of a 24-year-old female individual is A) $19.80 B) $19,800 C) $49.80 D) $49,800 Also provided are SST = 1,200 and SSE = 384. -Refer to Exhibit 15-8.The yearly income of a 24-year-old female individual is


A) $19.80
B) $19,800
C) $49.80
D) $49,800

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A regression model involved 18 independent variables and 200 observations.The critical value of t for testing the significance of each of the independent variable's coefficients will have


A) 18 degrees of freedom
B) 200 degrees of freedom
C) 199 degrees of freedom
D) 181 degrees of freedom

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