Question 1

In multiple regression analysis, the word "linear" in the term "general linear model" refers to the fact that

Accepted Answer

A) $\beta$0, $\beta$1, . . . $\beta$p, all have exponents of 0 
B) $\beta$0, $\beta$1, . . . $\beta$p, all have exponents of 1 
C) $\beta$0, $\beta$1, . . . $\beta$p, all have exponents of at least 1 
D) $\beta$0, $\beta$1, . . . $\beta$p, all have exponents of less than 1 
A) $\beta$0, $\beta$1, . . . $\beta$p, all have exponents of 0 
B) $\beta$0, $\beta$1, . . . $\beta$p, all have exponents of 1 
C) $\beta$0, $\beta$1, . . . $\beta$p, all have exponents of at least 1 
D) $\beta$0, $\beta$1, . . . $\beta$p, all have exponents of less than 1

Question 2

Exhibit 16-1
In a regression analysis involving 25 observations, the following estimated regression equation was developed.   = 10 - 18xS1U1B11S1U1B0 + 3xS1U1B12S1U1B0 + 14xS1U1B13S1U1B0
Also, the following standard errors and the sum of squares were obtained.SS1U1B1b1S1U1B0 = 3 SS1U1B1b2S1U1B0 = 6 SS1U1B1b3S1U1B0 = 7
SST = 4,800 SSE = 1,296
-Refer to Exhibit 16-1. The coefficient of x1

Accepted Answer

A) is significant 
B) is not significant 
C) cannot be tested, because not enough information is provided 
D) None of these alternatives is correct. 
A) is significant 
B) is not significant 
C) cannot be tested, because not enough information is provided 
D) None of these alternatives is correct.

Question 3

Consider the following data.   Use Excel's Regression Tool to estimate a general linear model of the form

Accepted Answer

The answer of Consider the following data.   Use...

Question 4

Exhibit 16-2
In a regression model involving 30 observations, the following estimated regression equation was obtained.   = 170 + 34xS1U1B11S1U1B0 - 3xS1U1B12S1U1B0 + 8xS1U1B13S1U1B0 + 58xS1U1B14S1U1B0 + 3xS1U1B15S1U1B0
For this model, SSR = 1,740 and SST = 2,000.
-Refer to Exhibit 16-2. The degrees of freedom associated with SST are

Accepted Answer

A) 24 
B) 6 
C) 19 
D) None of these alternatives is correct. 
A) 24 
B) 6 
C) 19 
D) None of these alternatives is correct.

Question 5

Exhibit 16-1
In a regression analysis involving 25 observations, the following estimated regression equation was developed.   = 10 - 18xS1U1B11S1U1B0 + 3xS1U1B12S1U1B0 + 14xS1U1B13S1U1B0
Also, the following standard errors and the sum of squares were obtained.SS1U1B1b1S1U1B0 = 3 SS1U1B1b2S1U1B0 = 6 SS1U1B1b3S1U1B0 = 7
SST = 4,800 SSE = 1,296
-Refer to Exhibit 16-1. If we are interested in testing for the significance of the relationship among the variables (i.e., significance of the model) the critical value of F at $\alpha$ = 0.05 is

Accepted Answer

A) 2.76 
B) 2.78 
C) 3.10 
D) 3.07 
A) 2.76 
B) 2.78 
C) 3.10 
D) 3.07

Question 6

A regression analysis (involving 45 observations) relating a dependent variable (y) and two independent variables resulted in the following information.   = 0.408 + 1.3387x1 + 2x2
The SSE for the above model is 49.When two other independent variables were added to the model, the following information was provided.   = 1.2 + 3.0x1 + 12x2 + 4.0x3 + 8x4
This latter model's SSE is 40.At a 5% significance level, test to determine if the two added independent variables contribute significantly to the model.

Accepted Answer

F = 4.5 > 3.23; Reje

Question 7

Monthly total production costs and the number of units produced at a local company over a period of 10 months are shown below.   
a.Draw a scatter diagram for the above data.
b.Assume that a model in the form of
y = $\beta$0 + $\beta$1+ $\varepsilon$
best describes the relationship between x and y. Estimate the parameters of this curvilinear regression equation.

Accepted Answer

a.Scatter diagram:
b

Question 8

The joint effect of two variables acting together is called

Accepted Answer

A) autocorrelation 
B) interaction 
C) serial correlation 
D) joint regression 
A) autocorrelation 
B) interaction 
C) serial correlation 
D) joint regression

Question 9

A soft drink manufacturer has developed a regression model relating sales (y in $10,000) with four independent variables. The four independent variables are price per unit (x1, in dollars), competitor's price (x2, in dollars), advertising (x3, in $1000) and type of container used (x4; 1 = Cans and 0 = Bottles). Part of the regression results are shown below. (Assume n = 25)   
a.If the manufacturer uses can containers and if his price is $1.25, his advertising expenditure is $200,000, and his competitor's price is $1.50, what is your estimate of his sales? (Give your answer in dollars.)
b.Test to see if there is a significant relationship between sales and unit price. Let $\alpha$ = 0.05.
c.Test to see if there is a significant relationship between sales and advertising. Let $\alpha$ = 0.05.
d.Is the type of container a significant variable? Let $\alpha$ = 0.05 = 0.05.
e.Test to see if there is a significant relationship between sales and competitor's price. Let $\alpha$ = 0.05.

Accepted Answer

a.$3,228,490
b.t = -2.8 < -2.0

Question 10

Exhibit 16-2
In a regression model involving 30 observations, the following estimated regression equation was obtained.   = 170 + 34xS1U1B11S1U1B0 - 3xS1U1B12S1U1B0 + 8xS1U1B13S1U1B0 + 58xS1U1B14S1U1B0 + 3xS1U1B15S1U1B0
For this model, SSR = 1,740 and SST = 2,000.
-Refer to Exhibit 16-2. The value of MSE is

Accepted Answer

A) 348 
B) 10.40 
C) 10.83 
D) 32.13 
A) 348 
B) 10.40 
C) 10.83 
D) 32.13

Question 11

Serial correlation is

Accepted Answer

A) the correlation between serial numbers of products 
B) the same as autocorrelation 
C) the same as leverage 
D) None of these alternatives is correct. 
A) the correlation between serial numbers of products 
B) the same as autocorrelation 
C) the same as leverage 
D) None of these alternatives is correct.

Question 12

The correlation in error terms that arises when the error terms at successive points in time are related is termed

Accepted Answer

A) leverage 
B) multicorrelation 
C) autocorrelation 
D) parallel correlation 
A) leverage 
B) multicorrelation 
C) autocorrelation 
D) parallel correlation

Question 13

Multiple regression analysis was used to study the relationship between a dependent variable, y, and three independent variables x1, x2 and, x3. The following is a partial result of the regression analysis involving 20 observations.   
a.Compute the coefficient of determination.
b.Perform a t test and determine whether or not $\beta$1 is significantly different from zero ($\alpha$ = 0.05).
c.Perform a t test and determine whether or not $\beta$2 is significantly different from zero ($\alpha$ = 0.05).
d.Perform a t test and determine whether or not $\beta$3 is significantly different from zero ($\alpha$ = 0.05).
e.At $\alpha$ = 0.05, perform an F test and determine whether or not the regression model is significant.

Accepted Answer

a.0.3636
b.t = 5 > 2.12; signi

Question 14

Exhibit 16-4
In a laboratory experiment, data were gathered on the life span (y in months) of 33 rats, units of daily protein intake (xS1U1B11S1U1B0), and whether or not agent xS1U1B12S1U1B0 (a proposed life extending agent) was added to the rats diet (xS1U1B12S1U1B0 = 0 if agent xS1U1B12S1U1B0 was not added, and xS1U1B12S1U1B0 = 1 if agent was added.) From the results of the experiment, the following regression model was developed.   = 36 + 0.8xS1U1B11S1U1B0 - 1.7xS1U1B12S1U1B0
Also provided are SSR = 60 and SST = 180.
-Refer to Exhibit 16-4. From the above function, it can be said that the life expectancy of rats that were given agent x2 is

Accepted Answer

A) 1.7 months more than those who did not take agent x2 
B) 1.7 months less than those who did not take agent x2 
C) 0.8 months less than those who did not take agent x2 
D) 0.8 months more than those who did not take agent x2 
A) 1.7 months more than those who did not take agent x2 
B) 1.7 months less than those who did not take agent x2 
C) 0.8 months less than those who did not take agent x2 
D) 0.8 months more than those who did not take agent x2

Question 15

Monthly total production costs and the number of units produced at a local company over a period of 10 months are shown below.   Use Excel's Regression Tool to estimate a second-order model of the form

Accepted Answer

The answer of Monthly total production costs and the number...

Question 16

Excel's Regression tool can be used to perform the ____ procedure.

Accepted Answer

A) stepwise regression 
B) forward selection 
C) backward elimination 
D) best-subsets 
A) stepwise regression 
B) forward selection 
C) backward elimination 
D) best-subsets

Question 17

Which of the following tests is used to determine whether an additional variable makes a significant contribution to a multiple regression model?

Accepted Answer

A) a t test 
B) a Z test 
C) an F test 
D) a chi-square test 
A) a t test 
B) a Z test 
C) an F test 
D) a chi-square test

Question 18

Exhibit 16-2
In a regression model involving 30 observations, the following estimated regression equation was obtained.   = 170 + 34xS1U1B11S1U1B0 - 3xS1U1B12S1U1B0 + 8xS1U1B13S1U1B0 + 58xS1U1B14S1U1B0 + 3xS1U1B15S1U1B0
For this model, SSR = 1,740 and SST = 2,000.
-Refer to Exhibit 16-2. The computed F value for testing the significance of the above model is

Accepted Answer

A) 32.12 
B) 6.69 
C) 4.8 
D) 58 
A) 32.12 
B) 6.69 
C) 4.8 
D) 58

Question 19

The following estimated regression equation has been developed for the relationship between y, the dependent variable, and x, the independent variable.   The sample size for this regression model was 23, and SSR = 600 and SSE = 400. 
a.Compute the coefficient of determination.
b.Using $\alpha$ = .05, test for a significant relationship.

Accepted Answer

a.r<sup>2</sup> = 0.

Question 20

Exhibit 16-4
In a laboratory experiment, data were gathered on the life span (y in months) of 33 rats, units of daily protein intake (xS1U1B11S1U1B0), and whether or not agent xS1U1B12S1U1B0 (a proposed life extending agent) was added to the rats diet (xS1U1B12S1U1B0 = 0 if agent xS1U1B12S1U1B0 was not added, and xS1U1B12S1U1B0 = 1 if agent was added.) From the results of the experiment, the following regression model was developed.   = 36 + 0.8xS1U1B11S1U1B0 - 1.7xS1U1B12S1U1B0
Also provided are SSR = 60 and SST = 180.
-Refer to Exhibit 16-4. The life expectancy of a rat that was not given any protein and that did not take agent x2 is

Accepted Answer

A) 36.7 
B) 34.3 
C) 36 
D) 38.4 
A) 36.7 
B) 34.3 
C) 36 
D) 38.4

In multiple regression analysis, the word "linear" in the term "general linear model" refers to the fact that

Consider the following data. Use Excel's Regression Tool to estimate a general linear model of the form

Exhibit 16-2 In a regression model involving 30 observations, the following estimated regression equation was obtained. = 170 + 34x₁ - 3x₂ + 8x₃ + 58x₄ + 3x₅ For this model, SSR = 1,740 and SST = 2,000. -Refer to Exhibit 16-2. The degrees of freedom associated with SST are

The joint effect of two variables acting together is called

Exhibit 16-2 In a regression model involving 30 observations, the following estimated regression equation was obtained. = 170 + 34x₁ - 3x₂ + 8x₃ + 58x₄ + 3x₅ For this model, SSR = 1,740 and SST = 2,000. -Refer to Exhibit 16-2. The value of MSE is

Serial correlation is

The correlation in error terms that arises when the error terms at successive points in time are related is termed

Monthly total production costs and the number of units produced at a local company over a period of 10 months are shown below. Use Excel's Regression Tool to estimate a second-order model of the form

Excel's Regression tool can be used to perform the ____ procedure.

Which of the following tests is used to determine whether an additional variable makes a significant contribution to a multiple regression model?

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Tests of Goodness of Fit, Independence and Multiple Proportions

Experimental Design and Analysis of Variance

Simple Linear Regression

Multiple Regression

Time Series Analysis and Forecasting

Nonparametric Methods

Statistical Methods for Quality Control

Decision Analysis

Sample Survey

Filters

Exam 16: Regression Analysis: Model Building

In multiple regression analysis, the word "linear" in the term "general linear model" refers to the fact that

Consider the following data. Use Excel's Regression Tool to estimate a general linear model of the form

Exhibit 16-2 In a regression model involving 30 observations, the following estimated regression equation was obtained. = 170 + 34x1 - 3x2 + 8x3 + 58x4 + 3x5 For this model, SSR = 1,740 and SST = 2,000. -Refer to Exhibit 16-2. The degrees of freedom associated with SST are

The joint effect of two variables acting together is called

Exhibit 16-2 In a regression model involving 30 observations, the following estimated regression equation was obtained. = 170 + 34x1 - 3x2 + 8x3 + 58x4 + 3x5 For this model, SSR = 1,740 and SST = 2,000. -Refer to Exhibit 16-2. The value of MSE is

Serial correlation is

The correlation in error terms that arises when the error terms at successive points in time are related is termed

Monthly total production costs and the number of units produced at a local company over a period of 10 months are shown below. Use Excel's Regression Tool to estimate a second-order model of the form

Excel's Regression tool can be used to perform the ____ procedure.

Which of the following tests is used to determine whether an additional variable makes a significant contribution to a multiple regression model?

Exhibit 16-2 In a regression model involving 30 observations, the following estimated regression equation was obtained. = 170 + 34x1 - 3x2 + 8x3 + 58x4 + 3x5 For this model, SSR = 1,740 and SST = 2,000. -Refer to Exhibit 16-2. The computed F value for testing the significance of the above model is

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Tests of Goodness of Fit, Independence and Multiple Proportions

Experimental Design and Analysis of Variance

Simple Linear Regression

Multiple Regression

Time Series Analysis and Forecasting

Nonparametric Methods

Statistical Methods for Quality Control

Decision Analysis

Sample Survey

Filters

Exhibit 16-2 In a regression model involving 30 observations, the following estimated regression equation was obtained. = 170 + 34x₁ - 3x₂ + 8x₃ + 58x₄ + 3x₅ For this model, SSR = 1,740 and SST = 2,000. -Refer to Exhibit 16-2. The degrees of freedom associated with SST are

Exhibit 16-2 In a regression model involving 30 observations, the following estimated regression equation was obtained. = 170 + 34x₁ - 3x₂ + 8x₃ + 58x₄ + 3x₅ For this model, SSR = 1,740 and SST = 2,000. -Refer to Exhibit 16-2. The value of MSE is