Question 1

Consider the following data.   Use Excel's Regression Tool to estimate a second-order model of the form

Accepted Answer

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

Question 2

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 3

The variable selection procedure that identifies the best regression equation, given a specified number of independent variables, is

Accepted Answer

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

Question 4

Consider the following data.   
a.Draw a scatter diagram. Does the relationship between x and y appear to be linear?
b.Assume the relationship between x and y can best be given by
y = $\beta$0 + $\beta$1+ $\varepsilon$
Estimate the parameters of this curvilinear function.

Accepted Answer

a.Relationship appea

Question 5

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 coefficient of determination for this model is

Accepted Answer

A) 0.6923 
B) 0.1494 
C) 0.1300 
D) 0.8700 
A) 0.6923 
B) 0.1494 
C) 0.1300 
D) 0.8700

Question 6

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 7

A regression model relating the yearly income (y), age (x1), and the gender of the faculty member of a university (x2 = 1 if female and 0 if male) resulted in the following information.   = 5,000 + 1.2x1 + 0.9x2
n = 20 SSE = 500 SSR = 1,500
Sb1 = 0.2 Sb2 = 0.1 
a.Is gender a significant variable?
b.Determine the multiple coefficient of determination.

Accepted Answer

a.t = 9 >

Question 8

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 SSE is

Accepted Answer

A) 3,740 
B) 170 
C) 260 
D) 2000 
A) 3,740 
B) 170 
C) 260 
D) 2000

Question 9

The following regression model y = $\beta$0 + $\beta$1x1 + $\beta$2x2 + $\varepsilon$
Is known as

Accepted Answer

A) first-order model with one predictor variable 
B) second-order model with two predictor variables 
C) second-order model with one predictor variable 
D) None of these alternatives is correct. 
A) first-order model with one predictor variable 
B) second-order model with two predictor variables 
C) second-order model with one predictor variable 
D) None of these alternatives is correct.

Question 10

We are interested in determining what type of model best describes the relationship between two variables x and y.
a.For a given data set, an estimated regression equation relating x and y of the formwas developed, using Excel. The results are shown below. Comment on the adequacy of this equation for predicting y. Let $\alpha$ = .05.     
b.An estimated regression equation for the same data set (as in part a) of the formwas developed. The Excel output is shown below. Comment on the adequacy of this equation for predicting y. Let $\alpha$ = .05.   
c.Use the results of Part b and predict y when x = 4.

Accepted Answer

a.= 2.7857 + 0.4643 x, r² = 0

Question 11

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 model

Accepted Answer

A) is significant 
B) is not significant 
C) Not enough information is provided to answer this question. 
D) None of these alternatives is correct. 
A) is significant 
B) is not significant 
C) Not enough information is provided to answer this question. 
D) None of these alternatives is correct.

Question 12

Which of the following statements about the backward elimination procedure is false?

Accepted Answer

A) It is a one-variable-at-a-time procedure. 
B) It begins with the regression model found using the forward selection procedure. 
C) It does not permit an independent variable to be reentered once it has been removed. 
D) It does not guarantee that the best regression model will be found. 
A) It is a one-variable-at-a-time procedure. 
B) It begins with the regression model found using the forward selection procedure. 
C) It does not permit an independent variable to be reentered once it has been removed. 
D) It does not guarantee that the best regression model will be found.

Question 13

Multiple regression analysis was used to study the relationship between a dependent variable, y, and four independent variables; x1, x2, x3 and, x4. The following is a partial result of the regression analysis involving 31 observations.   
a.Compute the coefficient of determination.
b.At $\alpha$ = 0.05, perform an F test and determine whether or not the regression model is significant.
c.Perform a t test and determine whether or not $\beta$1 is significantly different from zero ($\alpha$ = 0.05).
d.Perform a t test and determine whether or not $\beta$4 is significantly different from zero ($\alpha$ = 0.05).

Accepted Answer

a.0.6579
b.F = 12.5 > 2.74; si

Question 14

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 MSR is

Accepted Answer

A) 10.40 
B) 348 
C) 10.83 
D) 52 
A) 10.40 
B) 348 
C) 10.83 
D) 52

Question 15

The forward selection procedure starts with how many independent variable(s) in the multiple regression model?

Accepted Answer

A) none 
B) one 
C) two 
D) all of them 
A) none 
B) one 
C) two 
D) all of them

Question 16

Part of an Excel output relating y (dependent variable) and 4 independent variables, x1 through x4, is shown below.   
a.Fill in all the blanks marked with "?"
b.At a 5% significance level, which independent variables are significant and which ones are not? Fully explain how you arrived at your answers.

Accepted Answer

a. @#IMG-DLM& b.x₁ through x₃ are signific

Question 17

Exhibit 16-3
Below you are given a partial Excel output based on a sample of 25 observations.  
-Refer to Exhibit 16-3. The critical 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 
A) 2.06 
B) 2.069 
C) 2.074 
D) 2.080

Question 18

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 multiple coefficient of determination is

Accepted Answer

A) 0.27 
B) 0.73 
C) 0.50 
D) 0.33 
A) 0.27 
B) 0.73 
C) 0.50 
D) 0.33

Question 19

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 SSE are

Accepted Answer

A) 24 
B) 6 
C) 19 
D) 5 
A) 24 
B) 6 
C) 19 
D) 5

Question 20

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 x2

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.

Consider the following data. Use Excel's Regression Tool to estimate a second-order model of the form

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

The variable selection procedure that identifies the best regression equation, given a specified number of independent variables, is

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 coefficient of determination for this model is

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 value of SSE is

The following regression model y = $\beta$ ₀ + $\beta$ ₁x₁ + $\beta$ ₂x² + $\varepsilon$ Is known as

Which of the following statements about the backward elimination procedure is false?

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 MSR is

The forward selection procedure starts with how many independent variable(s) in the multiple regression model?

Exhibit 16-3 Below you are given a partial Excel output based on a sample of 25 observations. -Refer to Exhibit 16-3. The critical t value obtained from the table to test an individual parameter at the 5% level is

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 SSE are

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

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Sample Survey

Filters

Exam 16: Regression Analysis: Model Building

Consider the following data. Use Excel's Regression Tool to estimate a second-order model of the form

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

The variable selection procedure that identifies the best regression equation, given a specified number of independent variables, is

Consider the following data. a.Draw a scatter diagram. Does the relationship between x and y appear to be linear? b.Assume the relationship between x and y can best be given by y = β\betaβ 0 + β\betaβ 1+ ε\varepsilonε Estimate the parameters of this curvilinear function.

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 coefficient of determination for this model is

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 value of SSE is

The following regression model y = β\betaβ 0 + β\betaβ 1x1 + β\betaβ 2x2 + ε\varepsilonε Is known as

Which of the following statements about the backward elimination procedure is false?

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 MSR is

The forward selection procedure starts with how many independent variable(s) in the multiple regression model?

Exhibit 16-3 Below you are given a partial Excel output based on a sample of 25 observations. -Refer to Exhibit 16-3. The critical t value obtained from the table to test an individual parameter at the 5% level is

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 SSE are

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 coefficient of determination for this model is

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 SSE is

The following regression model y = $\beta$ ₀ + $\beta$ ₁x₁ + $\beta$ ₂x² + $\varepsilon$ Is known as

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 MSR is

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 SSE are