Question 1

In a multiple regression model, the error term F1F1F1S1F1F1F10 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 
A) have a mean of 1 
B) have a variance of zero 
C) have a standard deviation of 1 
D) be normally distributed

Question 2

Exhibit 13-8
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).   = 30 + 0.7xS1U1B11S1U1B0 + 3xS1U1B12S1U1B0
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 
A) 0.32 
B) 0.42 
C) 0.68 
D) 0.50

Question 3

The prices of Rawlston, Inc. stock (y) over a period of 12 days, the number of shares (in 100s) of company's stocks sold (x1), and the volume of exchange (in millions) on the New York Stock Exchange (x2) are shown below.
   Excel was used to determine the least-squares regression equation. Part of the computer output is shown below.
   
a.Use the output shown above and write an equation that can be used to predict the price of the stock.
b.Interpret the coefficients of the estimated regression equation that you found in Part
c.At 95% confidence, determine which variables are significant and which are not.
d.If in a given day, the number of shares of the company that were sold was 94,500 and the volume of exchange on the New York Stock Exchange was 16 million, what would you expect the price of the stock to be?

Accepted Answer

a.@#IMG-DLM&= 118.5055 - 0.0163x₁ - 1.5726x₂ b.As th

Question 4

Below you are given a partial Excel 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 2650 and the price of the competitor is $45, what would you expect the price of the stock to be?
c.At F1F1F1S1F1F1F10 = 0.05, test to determine if the Dow Jones average is a significant variable.
d.At F1F1F1S1F1F1F10 = 0.05, test to determine if the stock price of the major competitor is a significant variable.

Accepted Answer

a.@#IMG-DLM&= 20 + 0.03x₁ - 0.7x₂ b.$68 c.

Question 5

A regression model involving 3 independent variables for a sample of 20 periods resulted in the following sum of squares.
   
a.Compute the coefficient of determination and fully explain its meaning.
b.At F1F1F1S1F1F1F10 = 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

a.0.4737; 47.37% of variation

Question 6

Exhibit 13-8
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).   = 30 + 0.7xS1U1B11S1U1B0 + 3xS1U1B12S1U1B0
Also provided are SST = 1,200 and SSE = 384.
-Refer to Exhibit 13-8. 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 
A) $19.80 
B) $19,800 
C) $49.80 
D) $49,800

Question 7

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

Question 8

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

Accepted Answer

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

Question 9

Exhibit 13-6
Below you are given a partial Excel output based on a sample of 16 observations.
  
-Refer to Exhibit 13-6. Carry out the test to determine if there is a relationship among the variables at the 5% level. The null hypothesis should

Accepted Answer

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

Question 10

Unlike a simple linear regression model, a multiple regression model has more than one

Accepted Answer

A) intercept 
B) dependent variable 
C) independent variable 
D) error term 
A) intercept 
B) dependent variable 
C) independent variable 
D) error term

Question 11

Exhibit 13-7
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 13-7. The test statistic from the information provided is

Accepted Answer

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

Question 12

Exhibit 13-6
Below you are given a partial Excel output based on a sample of 16 observations.
  
-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 
A) 2 
B) 3 
C) 13 
D) 15

Question 13

A regression analysis involved 6 independent variables and 27 observations. The critical value of t for testing the significance of each of the independent variable's coefficients will have

Accepted Answer

A) 27 degrees of freedom 
B) 26 degrees of freedom 
C) 21 degrees of freedom 
D) 20 degrees of freedom 
A) 27 degrees of freedom 
B) 26 degrees of freedom 
C) 21 degrees of freedom 
D) 20 degrees of freedom

Question 14

In multiple regression analysis, the correlation among the independent variables is termed

Accepted Answer

A) homoscedasticity 
B) linearity 
C) multicollinearity 
D) adjusted coefficient of determination 
A) homoscedasticity 
B) linearity 
C) multicollinearity 
D) adjusted coefficient of determination

Question 15

The mathematical equation that explains how the dependent variable y is related to several independent variables x1, x2, ..., xp and the error term F1F1F1S1F1F1F10 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 
A) a simple nonlinear regression model 
B) a multiple regression model 
C) an estimated multiple regression equation 
D) a multiple regression equation

Question 16

Exhibit 13-7
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 13-7. The coefficient of determination is

Accepted Answer

A) 0.3636 
B) 0.7333 
C) 0.275 
D) 0.5 
A) 0.3636 
B) 0.7333 
C) 0.275 
D) 0.5

Question 17

In a multiple regression analysis involving 5 independent variables and 30 observations, SSR = 360 and SSE = 40. The coefficient of determination is

Accepted Answer

A) 0.80 
B) 0.90 
C) 0.25 
D) 0.15 
A) 0.80 
B) 0.90 
C) 0.25 
D) 0.15

Question 18

Exhibit 13-2
A regression model between sales (y in $1,000), unit price (xS1U1B11S1U1B0 in dollars) and television advertisement (xS1U1B12S1U1B0 in dollars) resulted in the following function:   = 7 - 3xS1U1B11S1U1B0 + 5xS1U1B12S1U1B0
For this model SSR = 3500, SSE = 1500, and the sample size is 18.
-Refer to Exhibit 13-2. If SSR = 600 and SSE = 300, the test statistic F is

Accepted Answer

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

Question 19

Exhibit 13-7
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 13-7. If we want to test for the significance of the model at 95% confidence, the critical F value (from the table) is

Accepted Answer

A) 3.06 
B) 3.48 
C) 3.34 
D) 3.11 
A) 3.06 
B) 3.48 
C) 3.34 
D) 3.11

Question 20

Exhibit 13-6
Below you are given a partial Excel output based on a sample of 16 observations.
  
-Refer to Exhibit 13-6. The estimated regression equation is

Accepted Answer

A) y = F1F1F1S1F1F1F100 + F1F1F1S1F1F1F101x1 + F1F1F1S1F1F1F102x2 + F1F1F1S1F1F1F10 
B) E(y) = F1F1F1S1F1F1F100 + F1F1F1S1F1F1F101x1 + F1F1F1S1F1F1F102x2 
C)  = 12.924 - 3.682 x1 + 45.216 x2 
D)  = 4.425 + 2.63 x1 + 12.56 x2 
A) y = F1F1F1S1F1F1F100 + F1F1F1S1F1F1F101x1 + F1F1F1S1F1F1F102x2 + F1F1F1S1F1F1F10 
B) E(y) = F1F1F1S1F1F1F100 + F1F1F1S1F1F1F101x1 + F1F1F1S1F1F1F102x2 
C)  = 12.924 - 3.682 x1 + 45.216 x2 
D)  = 4.425 + 2.63 x1 + 12.56 x2

In a multiple regression model, the error term  is assumed to

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

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

Exhibit 13-6 Below you are given a partial Excel output based on a sample of 16 observations. -Refer to Exhibit 13-6. Carry out the test to determine if there is a relationship among the variables at the 5% level. The null hypothesis should

Unlike a simple linear regression model, a multiple regression model has more than one

Exhibit 13-7 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 13-7. The test statistic from the information provided is

Exhibit 13-6 Below you are given a partial Excel output based on a sample of 16 observations. -Refer to Exhibit 13-6. The degrees of freedom for the sum of squares explained by the regression (SSR) are

A regression analysis involved 6 independent variables and 27 observations. The critical value of t for testing the significance of each of the independent variable's coefficients will have

In multiple regression analysis, the correlation among the independent variables is termed

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

Exhibit 13-7 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 13-7. The coefficient of determination is

In a multiple regression analysis involving 5 independent variables and 30 observations, SSR = 360 and SSE = 40. The coefficient of determination is

Exhibit 13-7 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 13-7. If we want to test for the significance of the model at 95% confidence, the critical F value (from the table) is

Exhibit 13-6 Below you are given a partial Excel output based on a sample of 16 observations. -Refer to Exhibit 13-6. The estimated regression equation is

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Exam 13: Multiple Regression

In a multiple regression model, the error term  is assumed to

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

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

Exhibit 13-6 Below you are given a partial Excel output based on a sample of 16 observations. -Refer to Exhibit 13-6. Carry out the test to determine if there is a relationship among the variables at the 5% level. The null hypothesis should

Unlike a simple linear regression model, a multiple regression model has more than one

Exhibit 13-7 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 13-7. The test statistic from the information provided is

Exhibit 13-6 Below you are given a partial Excel output based on a sample of 16 observations. -Refer to Exhibit 13-6. The degrees of freedom for the sum of squares explained by the regression (SSR) are

A regression analysis involved 6 independent variables and 27 observations. The critical value of t for testing the significance of each of the independent variable's coefficients will have

In multiple regression analysis, the correlation among the independent variables is termed

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

Exhibit 13-7 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 13-7. The coefficient of determination is

In a multiple regression analysis involving 5 independent variables and 30 observations, SSR = 360 and SSE = 40. The coefficient of determination is

Exhibit 13-7 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 13-7. If we want to test for the significance of the model at 95% confidence, the critical F value (from the table) is

Exhibit 13-6 Below you are given a partial Excel output based on a sample of 16 observations. -Refer to Exhibit 13-6. The estimated regression equation is

Data and Statistics

Descriptive Statistics: Tabular and Graphical Presentations

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Comparisons Involving Means, Experimental Design, and Analysis of Variance

Comparisons Involving Proportions and a Test of Independence

Simple Linear Regression

Statistical Methods for Quality Control

Time Series Analysis and Forecastng

Filters

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