Question 1

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

Accepted Answer

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

Question 2

Exhibit 15-5
Below you are given a partial Minitab output based on a sample of 25 observations. 
-Refer to Exhibit 15-5. The interpretation of the coefficient on X1 is that

Accepted Answer

A) a one unit change in X1 will lead to a 25.625 unit change in Y 
B) a one unit change in X1 will lead to a 25.625 unit increase in Y when all other variables are held constant 
C) a one unit change in X1 will lead to a 25.625 unit increase in X2 when all other variables are held constant 
D) It is impossible to interpret the coefficient.

Question 3

Exhibit 15-7
A regression model involving 4 independent variables and a sample of 15 periods resulted in the following sum of squares.
SSR = 165
SSE = 60
-Refer to Exhibit 15-7. The test statistic from the information provided is

Accepted Answer

A) 2.110 
B) 3.480 
C) 4.710 
D) 6.875

Question 4

Exhibit 15-5
Below you are given a partial Minitab output based on a sample of 25 observations. 
-Refer to Exhibit 15-5. The t value obtained from the table to test an individual parameter at the 5% level is

Accepted Answer

A) 2.06 
B) 2.069 
C) 2.074 
D) 2.080

Question 5

Exhibit 15-5
Below you are given a partial Minitab output based on a sample of 25 observations. 
-Refer to Exhibit 15-5. The estimated regression equation is

Accepted Answer

A)   
B)   
C)   
D)

Question 6

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. MSR for this model is

Accepted Answer

A) 200 
B) 10 
C) 1,000 
D) 43

Question 7

Exhibit 15-3
In a regression model involving 30 observations, the following estimated regression equation was obtained:  For this model SSR = 700 and SSE = 100.
-Refer to Exhibit 15-3. 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 8

Exhibit 15-8
The following estimated regression model was developed relating yearly income (Y in $1,000s) of 30 individuals with their age (XS1U1B11S1U1B0) and their gender (XS1U1B12S1U1B0) (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

Accepted Answer

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

Question 9

Exhibit 15-6
Below you are given a partial computer output based on a sample of 16 observations. 
-Refer to Exhibit 15-6. 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 10

In a multiple regression model, the error term $\varepsilon$ is assumed to

Accepted Answer

A) have a mean of 1 
B) have a variance of zero 
C) have a standard deviation of 1 
D) be normally distributed

Question 11

The mathematical equation that explains how the dependent variable y is related to several independent variables x1, x2, ......, xp and the error term $\varepsilon$ is

Accepted Answer

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

Question 12

Exhibit 15-5
Below you are given a partial Minitab output based on a sample of 25 observations. 
-Refer to Exhibit 15-5. We want to test whether the parameter $\beta$1 is significant. The test statistic equals

Accepted Answer

A) 0.357 
B) 2.8 
C) 14 
D) 1.96

Question 13

In a situation where the dependent variable can assume only one of the two possible discrete values,

Accepted Answer

A) we must use multiple regression 
B) there can only be two independent variables 
C) logistic regression should be applied 
D) all the independent variables must have values of either zero or one

Question 14

In multiple regression analysis,

Accepted Answer

A) there can be any number of dependent variables but only one independent variable 
B) there must be only one independent variable 
C) the coefficient of determination must be larger than 1 
D) there can be several independent variables, but only one dependent variable

Question 15

A student used multiple regression analysis to study how family spending (Y) is influenced by income (X₁), family size (X₂), and additions to savings (X₃). The variables Y, X₁, and X₃ are measured in thousands of dollars. The following results were obtained. a.Write out the estimated regression equation for the relationship between the variables. b.Compute R². What can you say about the strength of this relationship? c.Carry out a test of whether Y is significantly related to the independent variables. Use a .05 level of significance. d.Carry out a test to see if X₃ and Y are significantly related. Use a .05 level of significance.

Accepted Answer

The answer of A student used multiple regression analysis to...

Question 16

A sample of 30 houses that were sold in the last year was taken. The value of the house (Y) was estimated. The independent variables included in the analysis were the number of rooms (X₁), the size of the lot (X₂), the number of bathrooms (X₃), and a dummy variable (X₄), which equals 0 if the house does not have a garage and equals 1 otherwise. The following results were obtained: a. Write out the estimated equation. b. Interpret the coefficient on the number of rooms (X1). c. Interpret the coefficient on the dummy variable (X4). d. What are the degrees of freedom for the sum of squares explained by the regression (SSR) and the sum of squares due to error (SSE)? e. Test whether or not there is a significant relationship between the value of a house and the independent variables. Use a .05 level of significance. Be sure to state the null and alternative hypotheses. f. Test the significance of ?1 at the 5% level. Be sure to state the null and alternative hypotheses. g. Compute the coefficient of determination and interpret its meaning. h. Estimate the value of a house that has 9 rooms, a lot with an area of 7,500, 2 bathrooms, and 2 garages. b.Interpret the coefficient on the number of rooms (X₁). c.Interpret the coefficient on the dummy variable (X₄). d.What are the degrees of freedom for the sum of squares explained by the regression (SSR) and the sum of squares due to error (SSE)? e.Test whether or not there is a significant relationship between the value of a house and the independent variables. Use a .05 level of significance. Be sure to state the null and alternative hypotheses.

Accepted Answer

The answer of A sample of 30 houses that were...

Question 17

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). 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 $\alpha$ = 0.05, test to determine if the Dow Jones average is a significant variable. d.At $\alpha$ = 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...

Question 18

Exhibit 15-6
Below you are given a partial computer output based on a sample of 16 observations. 
-Refer to Exhibit 15-6. Carry out the test of significance for the parameter $\beta$1 at the 1% level. The null hypothesis should be

Accepted Answer

A) rejected 
B) not rejected 
C) revised 
D) None of these alternatives is correct.

Question 19

Shown below is a partial computer output from a regression analysis. a.Use the above results and write the regression equation. b.Compute the coefficient of determination and fully interpret its meaning. c.At $\alpha$ = 0.05, test to see if there is a relation between X₁ and Y. d.At $\alpha$ = 0.05, test to see if there is a relation between X₃ and Y. e.Is the regression model significant? Perform an F test and let $\alpha$ = 0.05.

Accepted Answer

The answer of Shown below is a partial computer output...

Question 20

A regression analysis involved 8 independent variables and 99 observations. The critical value of t for testing the significance of each of the independent variable's coefficients will have

Accepted Answer

A) 98 degrees of freedom 
B) 97 degrees of freedom 
C) 90 degrees of freedom 
D) 7 degrees of freedom

Exam 15: Multiple Regression

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

Exhibit 15-5 Below you are given a partial Minitab output based on a sample of 25 observations. -Refer to Exhibit 15-5. The interpretation of the coefficient on X₁ is that

Exhibit 15-7 A regression model involving 4 independent variables and a sample of 15 periods resulted in the following sum of squares. SSR = 165 SSE = 60 -Refer to Exhibit 15-7. The test statistic from the information provided is

Exhibit 15-5 Below you are given a partial Minitab output based on a sample of 25 observations. -Refer to Exhibit 15-5. The t value obtained from the table to test an individual parameter at the 5% level is

Exhibit 15-5 Below you are given a partial Minitab output based on a sample of 25 observations. -Refer to Exhibit 15-5. The estimated regression equation is

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. MSR for this model is

Exhibit 15-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: For this model SSR = 700 and SSE = 100. -Refer to Exhibit 15-3. The conclusion is that the

Exhibit 15-6 Below you are given a partial computer output based on a sample of 16 observations. -Refer to Exhibit 15-6. The degrees of freedom for the sum of squares explained by the regression (SSR) are

In a multiple regression model, the error term $\varepsilon$ is assumed to

The mathematical equation that explains how the dependent variable y is related to several independent variables x₁, x₂, ......, x_p and the error term $\varepsilon$ is

In a situation where the dependent variable can assume only one of the two possible discrete values,

In multiple regression analysis,

A regression analysis involved 8 independent variables and 99 observations. The critical value of t for testing the significance of each of the independent variable's coefficients will have

Exam 15: Multiple Regression

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

Exhibit 15-5 Below you are given a partial Minitab output based on a sample of 25 observations. -Refer to Exhibit 15-5. The interpretation of the coefficient on X1 is that

Exhibit 15-7 A regression model involving 4 independent variables and a sample of 15 periods resulted in the following sum of squares. SSR = 165 SSE = 60 -Refer to Exhibit 15-7. The test statistic from the information provided is

Exhibit 15-5 Below you are given a partial Minitab output based on a sample of 25 observations. -Refer to Exhibit 15-5. The t value obtained from the table to test an individual parameter at the 5% level is

Exhibit 15-5 Below you are given a partial Minitab output based on a sample of 25 observations. -Refer to Exhibit 15-5. The estimated regression equation is

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. MSR for this model is

Exhibit 15-3 In a regression model involving 30 observations, the following estimated regression equation was obtained: For this model SSR = 700 and SSE = 100. -Refer to Exhibit 15-3. The conclusion is that the

Exhibit 15-6 Below you are given a partial computer output based on a sample of 16 observations. -Refer to Exhibit 15-6. The degrees of freedom for the sum of squares explained by the regression (SSR) are

In a multiple regression model, the error term ε\varepsilonε is assumed to

The mathematical equation that explains how the dependent variable y is related to several independent variables x1, x2, ......, xp and the error term ε\varepsilonε is

Exhibit 15-5 Below you are given a partial Minitab output based on a sample of 25 observations. -Refer to Exhibit 15-5. We want to test whether the parameter β\betaβ 1 is significant. The test statistic equals

In a situation where the dependent variable can assume only one of the two possible discrete values,

In multiple regression analysis,

Exhibit 15-6 Below you are given a partial computer output based on a sample of 16 observations. -Refer to Exhibit 15-6. Carry out the test of significance for the parameter β\betaβ 1 at the 1% level. The null hypothesis should be

A regression analysis involved 8 independent variables and 99 observations. The critical value of t for testing the significance of each of the independent variable's coefficients will have

Exhibit 15-5 Below you are given a partial Minitab output based on a sample of 25 observations. -Refer to Exhibit 15-5. The interpretation of the coefficient on X₁ is that

In a multiple regression model, the error term $\varepsilon$ is assumed to

The mathematical equation that explains how the dependent variable y is related to several independent variables x₁, x₂, ......, x_p and the error term $\varepsilon$ is