Question 1

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 C

Question 2

The following regression model y = β0 + β1x1 + β2x2 + ε 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 the answers 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 the answers is correct. C

Question 3

Consider the following data: $$\begin{array} { l l } 
x & y \
1 & 2 \
4 & 3 \
6 & 5 \
7 & 8 \
8 & 10
\end{array}$$ Use Excel's Regression tool to estimate a general linear model that uses a reciprocal transformation on the dependent variable.
​

Accepted Answer

\(\begin{array}{|l|l|l|l|l|l|l|}
\hline & \text { A } & \text { B } & \text { C } & \text { D } & \text { E }& \text { F } \
\hline 1 & \mathrm{y} & \mathrm{x} & 1 / \mathrm{y} \
\hline 2 & 2 & 1 & 0.5000 \
\hline 3 & 3 & 4 & 0.3333 \
\hline 4 & 5 & 6 & 0.2000 \
\hline 5 & 8 & 7 & 0.1250 \
\hline 6 & 10 & 8 & 0.1000 \
\hline 7 & & & \
\hline 8 & \text { SUMMARY OUTPUT } & & \
\hline 9 & & \
\hline 10 & \text { Regression Statistics } & \
\hline \mathbf{1 1} & \text { MultipleR } & 0.99668 \
\hline 12 & \text { R Square } & 0.99337 \
\hline \mathbf{1 3} & \text { Adjusted R Square } & 0.99116 \
\hline 14 & \text { Standard Error } & 0.01560 \
\hline 15 & \text { Observations } & 5 \\hline16\
\hline17 &\text { ANOVA }\
\hline 18 & & d f & S S & M S & F & \text { Signif. F } \
\hline 19 & \text { Regression } & 1 & 0.10933 & 0.10933 & 449.241 & 0.00023 \
\hline 20 & \text { Residual } & 3 & 0.00073 & 0.00024 & & \
\hline 21 & \text { Total } & 4 & 0.11006 & & & \\hline22\
\hline 23 & & \text { Coefficients } & \text { Sta. Error } & \text { tStat } & \text { P-value } & \text { Lower 95\% } \
\hline 24 & \text { Intercept } & 0.56147 & 0.0162 & 34.6667 & 5.28 \mathrm{E}-05 & 0.50993 \
\hline 25 & \mathrm{x} & -0.05958 & 0.0028 & -21.1953 & 0.00023 & -0.06852\
\hline
\end{array}\) $$1 / y = .561472 - .05958 x$$

Question 4

All the variables in a multiple regression analysis _____.

Accepted Answer

A)  must be quantitative 
B)  must be either quantitative or qualitative but not a mix of both 
C)  must be positive 
D)  None of the answers is correct. 
A)  must be quantitative 
B)  must be either quantitative or qualitative but not a mix of both 
C)  must be positive 
D)  None of the answers is correct.

Question 5

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 6

What value of Durbin-Watson statistic indicates no autocorrelation is present?

Accepted Answer

A)  1 
B)  2 
C)  -2 
D)  0 
A)  1 
B)  2 
C)  -2 
D)  0

Question 7

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 8

A test to determine whether or not first-order autocorrelation is present is _____.

Accepted Answer

A)  a t test 
B)  the Durbin-Watson test 
C)  an F test 
D)  a chi-square test 
A)  a t test 
B)  the Durbin-Watson test 
C)  an F test 
D)  a chi-square test

Question 9

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 10

When a regression model was developed relating sales (y) of a company to its product's price (x1), the SSE was determined to be 495. A second regression model relating sales (y) to product's price (x1) and competitor's product price (x2) resulted in an SSE of 396. At α = .05, determine if the competitor's product price contributed significantly to the model. The sample size for both models was 33.

Accepted Answer

F = 7.5 > 4.17; x₂ co

Question 11

A regression model relating a dependent variable, y, with one independent variable, x1, resulted in an SSE of 400. Another regression model with the same dependent variable, y, and two independent variables, x1 and x2, resulted in an SSE of 320. At α = .05, determine if x2 contributed significantly to the model. The sample size for both models was 20.

Accepted Answer

F = 4.25 < 4.45; x₂ d

Question 12

Consider the following data: $$\begin{array} { c c } 
\mathrm { x } & \mathrm { y } \
4 & 8 \
6 & 10 \
8 & 8 \
10 & 12 \
14 & 4
\end{array}$$ ​
Use Excel's Regression tool to estimate a general linear model of the form $$\ln y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon$$

Accepted Answer

The answer of Consider the following data: \[\begin{array} { c...

Question 13

Monthly total production costs and the number of units produced at a local company over a period of 10 months are shown below. $$\begin{array} { ccc } 
\text { Month } & \text { Production Costs } \left( y _ { i } \right) & \text { Units Produced } \left( x _ { 1 } \right) \
&(\$ \text { millions) } &(\text { millions) } \
1 & 1 & 2 \
2 & 1 & 3 \
3 & 1 & 4 \
4 & 2 & 5 \
5 & 2 & 6 \
6 & 4 & 7 \
7 & 5 & 8 \
8 & 7 & 9 \
9 & 9 & 10 \
10 & 12 & 10
\end{array}$$ Use Excel's Regression tool to estimate a second-order model of the form $$y = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 1 } ^ { 2 } + \varepsilon$$ ​

Accepted Answer

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

Question 14

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

Question 15

Consider the following data: $$\begin{array} { r r } 
x & y \
1 & 2 \
4 & 3 \
6 & 5 \
7 & 8 \
8 & 10
\end{array}$$ Use Excel's Regression tool to estimate a general linear model of the form $$\ln y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon$$ ​

Accepted Answer

The answer of Consider the following data: \[\begin{array} { r...

Question 16

A regression analysis (involving 45 observations) relating a dependent variable (y) and two independent variables resulted in the following information.
​ $\widehat { y }$ = 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.
​ $\widehat { y }$ = 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 17

The range of the Durbin-Watson statistic is _____.

Accepted Answer

A)  -1 to 1 
B)  0 to 1 
C)  -∞ to ∞ 
D)  0 to 4 
A)  -1 to 1 
B)  0 to 1 
C)  -∞ to ∞ 
D)  0 to 4

Question 18

Forty-eight observations of a dependent variable (y) and five independent variables resulted in an SSE of 438. When two additional independent variables were added to the model, the SSE was reduced to 375. At a 5% level of significance, determine if the two additional independent variables contribute significantly to the model.

Accepted Answer

F = 3.36 > 3.23; Rej

Question 19

A sample of six recent college graduates shows their current annual income (in $1000s), years of education, and current age (in years). The data follow: $$\begin{array} { l l l } 
\text { Income } & \text { Education } & \text { Age } \
47.8 & 2 & 20 \
37.3 & 2 & 25 \
33.5 & 2 & 30 \
79 & 4 & 20 \
67 & 4 & 25 \
39.3 & 4 & 30
\end{array}$$ Use Excel's Regression tool to estimate a general linear model of the form that predicts annual income. $$y = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 1 } x _ { 2 } + \varepsilon$$ ​

Accepted Answer

The answer of A sample of six recent college graduates...

Question 20

When autocorrelation is present, one of the assumptions of the regression model is violated and that assumption is the _____.

Accepted Answer

A)  expected value of the error term ε is zero 
B)  variance of the error term ε is the same for all values of x 
C)  values of the error term ε are independent 
D)  values of the error term ε are normally distributed for all values of x 
A)  expected value of the error term ε is zero 
B)  variance of the error term ε is the same for all values of x 
C)  values of the error term ε are independent 
D)  values of the error term ε are normally distributed for all values of x

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

The following regression model y = β₀ + β₁x₁ + β₂x² + ε is known as _____.

Consider the following data: x y 1 2 4 3 6 5 7 8 8 10 Use Excel's Regression tool to estimate a general linear model that uses a reciprocal transformation on the dependent variable.

All the variables in a multiple regression analysis _____.

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

What value of Durbin-Watson statistic indicates no autocorrelation is present?

The joint effect of two variables acting together is called _____.

A test to determine whether or not first-order autocorrelation is present is _____.

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

Consider the following data: 4 8 6 10 8 8 10 12 14 4 Use Excel's Regression tool to estimate a general linear model of the form $\ln y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon$

Serial correlation is_____.

Consider the following data: x y 1 2 4 3 6 5 7 8 8 10 Use Excel's Regression tool to estimate a general linear model of the form $\ln y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon$

The range of the Durbin-Watson statistic is _____.

When autocorrelation is present, one of the assumptions of the regression model is violated and that assumption is the _____.

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

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

The following regression model y = β0 + β1x1 + β2x2 + ε is known as _____.

Consider the following data: x y 1 2 4 3 6 5 7 8 8 10 Use Excel's Regression tool to estimate a general linear model that uses a reciprocal transformation on the dependent variable. ​

All the variables in a multiple regression analysis _____.

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

What value of Durbin-Watson statistic indicates no autocorrelation is present?

The joint effect of two variables acting together is called _____.

A test to determine whether or not first-order autocorrelation is present is _____.

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

Consider the following data: 4 8 6 10 8 8 10 12 14 4 ​ Use Excel's Regression tool to estimate a general linear model of the form ln⁡y=β0+β1x+ε\ln y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilonlny=β0​+β1​x+ε

Serial correlation is_____.

Consider the following data: x y 1 2 4 3 6 5 7 8 8 10 Use Excel's Regression tool to estimate a general linear model of the form ln⁡y=β0+β1x+ε\ln y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilonlny=β0​+β1​x+ε ​

The range of the Durbin-Watson statistic is _____.

When autocorrelation is present, one of the assumptions of the regression model is violated and that assumption is the _____.

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

The following regression model y = β₀ + β₁x₁ + β₂x² + ε is known as _____.

Consider the following data: x y 1 2 4 3 6 5 7 8 8 10 Use Excel's Regression tool to estimate a general linear model that uses a reciprocal transformation on the dependent variable.

Consider the following data: 4 8 6 10 8 8 10 12 14 4 Use Excel's Regression tool to estimate a general linear model of the form $\ln y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon$

Consider the following data: x y 1 2 4 3 6 5 7 8 8 10 Use Excel's Regression tool to estimate a general linear model of the form $\ln y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon$