Question 1

Exhibit 13-5
Below you are given a partial Minitab output based on a sample of 25 observations.
 $\begin{array}{lcc}&\text { Coefficient }&\text { Standard Error }\
\text { Constant } & 145.321 & 48.682 \
\mathrm{X}_{1} & 25.625 & 9.150 \
\mathrm{X}_{2} & -5.720 & 3.575 \
\mathrm{X}_{3} & 0.823 & 0.183
\end{array}$
-Refer to Exhibit 13-5. The estimated regression equation is

Accepted Answer

A)  Y = ?? + ??X1 + ?2X2 + ?3X3 + ? 
B)  EY) = ?? + ??X1 + ?2X2 + ?3X3 
C)  =145.321+25.625X1 - 5.720X2+0.823X3 
D)  =48.682+9.15X1+3.575X2+1.183X3

Question 2

The adjusted multiple coefficient of determination is adjusted for

Accepted Answer

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

Question 3

The following model Y=β₀+β₁X1+ε is referred to as a

Accepted Answer

A)  curvilinear model 
B)  curvilinear model with one predictor variable 
C)  simple second-order model with one predictor variable 
D)  simple first-order model with one predictor variable

Question 4

Exhibit 13-3
In a regression model involving 30 observations, the following estimated regression equation was obtained:
 $\hat { Y }$ =17+4X1 - 3X2+8X3+8X4
For this model SSR = 700 and SSE = 100.
-Refer to Exhibit 13-3. The critical F value at 95% confidence is

Accepted Answer

A)  2.53 
B)  2.69 
C)  2.76 
D)  2.99

Question 5

A term used to describe the case when the independent variables in a multiple regression model are correlated is

Accepted Answer

A)  regression 
B)  correlation 
C)  multicollinearity 
D)  None of the above answers is correct.

Question 6

Exhibit 13-9
In a regression analysis involving 25 observations, the following estimated regression equation was developed.
 $\hat { Y }$ =10 - 18X1+3X2+14X3
Also, the following standard errors and the sum of squares were obtained.
Sb₁ = 3 Sb2 = 6 Sb3 = 7
SST = 4,800 SSE = 1,296
-Refer to Exhibit 13-9. If you want to determine whether or not the coefficients of the independent variables are significant, the critical value of t statistic at ? = 0.05 is

Accepted Answer

A)  2.080 
B)  2.060 
C)  2.064 
D)  1.96

Question 7

In a multiple regression analysis SSR = 1,000 and SSE = 200. The F statistic for this model is

Accepted Answer

A)  5.0 
B)  1,200 
C)  800 
D)  Not enough information is provided to answer this question.

Question 8

Exhibit 13-9
In a regression analysis involving 25 observations, the following estimated regression equation was developed.
 $\hat { Y }$ =10 - 18X1+3X2+14X3
Also, the following standard errors and the sum of squares were obtained.
Sb₁ = 3 Sb2 = 6 Sb3 = 7
SST = 4,800 SSE = 1,296
-Refer to Exhibit 13-9. The test statistic for testing the significance of the model is

Accepted Answer

A)  0.730 
B)  18.926 
C)  3.703 
D)  1.369

Question 9

Exhibit 13-8
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).
 $\hat { Y }$ =30+0.7X1+3X2
Also provided are SST = 1,200 and SSE = 384.
-Refer to Exhibit 13-8. The yearly income of a 24-year-old male individual is

Accepted Answer

A)  $13.80 
B)  $13,800 
C)  $46,800 
D)  $49,800

Question 10

The estimate of the multiple regression equation based on the sample data, which has the form of Ey) = $\hat { \mathrm { y } }$ = b? + b?x1 + b2x2 + ... + bpxp is

Accepted Answer

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

Question 11

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

Accepted Answer

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

Question 12

Exhibit 13-8
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).
 $\hat { Y }$ =30+0.7X1+3X2
Also provided are SST = 1,200 and SSE = 384.
-Refer to Exhibit 13-8. The multiple coefficient of determination is

Accepted Answer

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

Question 13

Exhibit 13-6
Below you are given a partial computer output based on a sample of 16 observations.
 $\begin{array}{lcc} 
& \text { Coefficient } & \text { Standard Error } \
\text { Intercept } & 12.924&4.425\
\mathrm{X}_{1} & -3.682&2.63. \
\mathrm{X}_{2} &45.216&12.560\
\end{array}$
$\text { Analysis of Variance }$

$\begin{array}{lccc}
\text { Source of } & \text { Degrees } &\text { Sum of } &\text { Mean }\
\text { Variation } & \text { of Freedom }&\text { Squares } & \text { Square }&F\
\text { Regression }&&4,853&2,426.5\
\text {Error }&&&485.3
\end{array}$
-Refer to Exhibit 13-6. The degrees of freedom for the sum of squares explained by the regression SSR) are

Accepted Answer

A)  2 
B)  3 
C)  13 
D)  15

Question 14

A multiple regression model has the form Y = 7 + 2X1 + 9X2 As X1 increases by 1 unit holding X2 constant), Y is expected to

Accepted Answer

A)  increase by 9 units 
B)  decrease by 9 units 
C)  increase by 2 units 
D)  decrease by 2 units

Question 15

A measure of goodness of fit for the estimated regression equation is the

Accepted Answer

A)  multiple coefficient of determination 
B)  mean square due to error 
C)  mean square due to regression 
D)  sample size

Question 16

Exhibit 13-6
Below you are given a partial computer output based on a sample of 16 observations.
 $\begin{array}{lcc} 
& \text { Coefficient } & \text { Standard Error } \
\text { Intercept } & 12.924&4.425\
\mathrm{X}_{1} & -3.682&2.63. \
\mathrm{X}_{2} &45.216&12.560\
\end{array}$
$\text { Analysis of Variance }$

$\begin{array}{lccc}
\text { Source of } & \text { Degrees } &\text { Sum of } &\text { Mean }\
\text { Variation } & \text { of Freedom }&\text { Squares } & \text { Square }&F\
\text { Regression }&&4,853&2,426.5\
\text {Error }&&&485.3
\end{array}$
-Refer to Exhibit 13-6. The test statistic used to determine if there is a relationship among the variables equals

Accepted Answer

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

Question 17

Exhibit 13-3
In a regression model involving 30 observations, the following estimated regression equation was obtained:
 $\hat { Y }$ =17+4X1 - 3X2+8X3+8X4
For this model SSR = 700 and SSE = 100.
-Refer to Exhibit 13-3. The conclusion is that the

Accepted Answer

A)  model is not significant 
B)  model is significant 
C)  slope of X1 is significant 
D)  slope of X2 is significant

Question 18

Exhibit 13-2
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:
 $\hat { Y }$ =7-3X1+5X2
For this model SSR = 3500, SSE = 1500, and the sample size is 18.
-Refer to Exhibit 13-2. To test for the significance of the model, the test statistic F is

Accepted Answer

A)  2.33 
B)  0.70 
C)  17.5 
D)  1.75

Question 19

A regression model involving 3 independent variables for a sample of 20 periods resulted in the following sum of squares.
Sum of Squares
Regression 90
Residual Error) 100
a. Compute the coefficient of determination and fully explain its meaning.
b. At α = 0.05 level of significance, test to determine whether or not there is a significant relationship between the independent variables and the dependent variable.

Accepted Answer

The answer of A regression model involving 3 independent variables...

Question 20

Below you are given a computer output based on a sample of 30 days of the price of a company's stock Y in dollars), the Dow Jones industrial average X1), and the stock price of the company's major competitor X2 in dollars).
 $\begin{array}{lr}
&\text { Coefilicient }&\text { Standard Error }\
\text { Constant } & 20.000 & 5.455 \
\mathrm{X}_{1} & 0.006 & 0.002 \
\mathrm{X}_{2} & -0.70 & 0.200
\end{array}$ 
a. Use the output shown above and write an equation that can be used to predict the price of the stock.
b. If the Dow Jones Industrial Average is 10,000 and the price of the competitor is $50, what would you expect the price of the stock to be?
c. At α = 0.05, test to determine if the Dow Jones average is a significant variable.
d. At α = 0.05, test to determine if the stock price of the major competitor is a significant variable.

Accepted Answer

The answer of Below you are given a computer output...

Exam 13: Multiple Regression

The adjusted multiple coefficient of determination is adjusted for

The following model Y=β₀+β₁X1+ε is referred to as a

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: $\hat { Y }$ =17+4X1 - 3X2+8X3+8X4 For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The critical F value at 95% confidence is

A term used to describe the case when the independent variables in a multiple regression model are correlated is

In a multiple regression analysis SSR = 1,000 and SSE = 200. The F statistic for this model is

The estimate of the multiple regression equation based on the sample data, which has the form of Ey) = $\hat { \mathrm { y } }$ = b? + b?x1 + b2x2 + ... + bpxp is

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 multiple regression model has the form Y = 7 + 2X1 + 9X2 As X1 increases by 1 unit holding X2 constant) , Y is expected to

A measure of goodness of fit for the estimated regression equation is the

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: $\hat { Y }$ =17+4X1 - 3X2+8X3+8X4 For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The conclusion is that the

Exam 13: Multiple Regression

The adjusted multiple coefficient of determination is adjusted for

The following model Y=β₀+β₁X1+ε is referred to as a

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: Y^\hat { Y }Y^ =17+4X1 - 3X2+8X3+8X4 For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The critical F value at 95% confidence is

A term used to describe the case when the independent variables in a multiple regression model are correlated is

In a multiple regression analysis SSR = 1,000 and SSE = 200. The F statistic for this model is

The estimate of the multiple regression equation based on the sample data, which has the form of Ey) = y^\hat { \mathrm { y } }y^​ = b? + b?x1 + b2x2 + ... + bpxp is

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 multiple regression model has the form Y = 7 + 2X1 + 9X2 As X1 increases by 1 unit holding X2 constant) , Y is expected to

A measure of goodness of fit for the estimated regression equation is the

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: Y^\hat { Y }Y^ =17+4X1 - 3X2+8X3+8X4 For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The conclusion is that the

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: $\hat { Y }$ =17+4X1 - 3X2+8X3+8X4 For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The critical F value at 95% confidence is

The estimate of the multiple regression equation based on the sample data, which has the form of Ey) = $\hat { \mathrm { y } }$ = b? + b?x1 + b2x2 + ... + bpxp is

Exhibit 13-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: $\hat { Y }$ =17+4X1 - 3X2+8X3+8X4 For this model SSR = 700 and SSE = 100. -Refer to Exhibit 13-3. The conclusion is that the