Question 1

The following ANOVA table is from a multiple regression analysis. $$\begin{array} { | c | c | c | c | c | c | } 
\hline \text { Source } & \mathrm { df } & \mathrm { SS } & \mathrm { MS } & F & p \
\hline \text { Repression } & 3 & 1500 & & & \
\hline \text { Error } & 26 & & & & \
\hline \text { Total } & & 2300 & & & \
\hline
\end{array}$$ The MSE value is closest to__________.

Accepted Answer

A) 31 
B) 500 
C) 16 
D) 2300 
E) 8.7 
A) 31 
B) 500 
C) 16 
D) 2300 
E) 8.7

Question 2

The following ANOVA table is from a multiple regression analysis. $$\begin{array} { | c | c | c | c | c | c | } 
\hline \text { Source } & \mathrm { df } & \mathrm { SS } & \mathrm { MS } & F & p \
\hline \text { Repression } & 3 & 1500 & & & \
\hline \text { Error } & 26 & & & & \
\hline \text { Total } & & 2300 & & & \
\hline
\end{array}$$ The observed F value is __________.

Accepted Answer

A) 16.25 
B) 30.77 
C) 500 
D) 0.049 
E) 0.039 
A) 16.25 
B) 30.77 
C) 500 
D) 0.049 
E) 0.039

Question 3

A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size, household income, and household neighborhood (urban, suburban, and rural).The "neighborhood" variable in this model is ______.

Accepted Answer

A) an independent variable 
B) a response variable 
C) a quantitative variable 
D) a dependent variable 
E) a constant 
A) an independent variable 
B) a response variable 
C) a quantitative variable 
D) a dependent variable 
E) a constant

Question 4

A multiple regression analysis produced the following output from Excel.   The correlation coefficient is ____________.

Accepted Answer

A) 0.9787 
B) 0.9579 
C) 0.9523 
D) 67.671 
E) 0.0489 
A) 0.9787 
B) 0.9579 
C) 0.9523 
D) 67.671 
E) 0.0489

Question 5

A multiple regression analysis produced the following tables. $$\begin{array} { | c | c | c | c | c | } 
\hline \text { Predictor } & \text { Coefficients } & \text { Stardard Eror } & \boldsymbol { t } \text { Statistic } & p \text {-value } \
\hline \text { Irtercept } & 616.6849 & 154.5534 & 3.990108 & 0.000947 \
\hline \boldsymbol { x } _ { 1 } & - 3.33833 & \mathbf { 2 . 3 3 3 5 4 8 } & - 1.43058 & \mathbf { 0 . 1 7 0 6 7 5 } \
\hline \mathbf { x } _ { 2 } & 1.780075 & \mathbf { 0 . 3 3 5 6 0 5 } & 5.30407 & 5.83 \mathrm { E } - 05 \
\hline
\end{array}$$ $$\begin{array} { | c | c | c | c | c | c | } 
\hline \text { Source } & \mathrm { df } & \text { SS } & \text { MS } & F & p \text {-value } \
\hline \text { Repression } & 2 & 121783 & 60891.48 & 14.76117 & 0.000286 \
\hline \text { Residual } & 15 & 61876.68 & 4125.112 & & \
\hline \text { Total } & 17 & 183659.6 & & & \
\hline
\end{array}$$ These results indicate that ____________.

Accepted Answer

A) none of the predictor variables are significant at the 5% level 
B) each predictor variable is significant at the 5% level 
C) x1 is significant at the 5% level 
D) x2 is significant at the 5% level 
E) the intercept is not significant at 5% level 
A) none of the predictor variables are significant at the 5% level 
B) each predictor variable is significant at the 5% level 
C) x1 is significant at the 5% level 
D) x2 is significant at the 5% level 
E) the intercept is not significant at 5% level

Question 6

Regression analysis with two dependent variables and two or more independent variables is called multiple regression.

Accepted Answer

A) True 
 B)False

Question 7

The following ANOVA table is from a multiple regression analysis. $$\begin{array} { | c | c | c | c | c | c | } 
\hline \text { Source } & \mathrm { df } & \mathrm { SS } & \mathrm { MS } & F & p \
\hline \text { Repression } & 3 & 1500 & & & \
\hline \text { Error } & 26 & & & & \
\hline \text { Total } & & 2300 & & & \
\hline
\end{array}$$ The R2 value is __________.

Accepted Answer

A) 0.65 
B) 0.53 
C) 0.35 
D) 0.43 
E) 1.37 
A) 0.65 
B) 0.53 
C) 0.35 
D) 0.43 
E) 1.37

Question 8

In a multiple regression model, the partial regression coefficient of an independent variable represents the increase in the y variable when that independent variable is increased by one unit if the values of all other independent variables are held constant.

Accepted Answer

A) True 
 B)False

Question 9

A multiple regression analysis produced the following tables. $$\begin{array} { | c | c | c | c | c | } 
\hline \text { Predictor } & \text { Coefficients } & \text { Stardard Error } & t \text { Statistic } & p \text {-value } \
\hline \text { Irtercept } & 512.2359 & 78.49712 & 7.956176 & 6.88 \mathrm { E } - 06 \
\hline \boldsymbol { x } _ { 1 } & 7.1525 & 1.652255 & 5.186319 & \mathbf { 0 . 0 0 0 3 0 1 } \
\hline \mathbf { x } _ { 2 } & \mathbf { 2 . 0 2 0 8 } & 0.699194 & 6.774248 & \mathbf { 3 . 0 6 E - 0 5 } \
\hline
\end{array}$$ $$\begin{array} { | c | c | c | c | c | c | } 
\hline \text { Source } & \mathrm { df } & \text { SS } & \text { MS } & F & p \text {-value } \
\hline \text { Repression } & 2 & 1660914 & \mathbf { 8 3 0 4 5 7 . 1 } & 58.31956 & 1.4 \mathrm { E } - 06 \
\hline \text { Residual } & 11 & 156637.5 & 14239.77 & & \
\hline \text { Total } & 13 & 1817552 & & & \
\hline
\end{array}$$ If x1= 25 and x2 = 85, then the predicted value of y is ____________.

Accepted Answer

A) 803.891 
B) 807.255 
C) 812.025 
D) 825.517 
E) 862.816 
A) 803.891 
B) 807.255 
C) 812.025 
D) 825.517 
E) 862.816

Question 10

In the model y = $\beta$ 0 + $\beta$ 1x1 + $\beta$ 2x2 +$\beta$ 3x3 + $\varepsilon$,$\varepsilon$ is a constant.

Accepted Answer

A) True 
 B)False

The following ANOVA table is from a multiple regression analysis. Source F p Repression 3 1500 Error 26 Total 2300 The MSE value is closest to__________.

The following ANOVA table is from a multiple regression analysis. Source F p Repression 3 1500 Error 26 Total 2300 The observed F value is __________.

A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size, household income, and household neighborhood (urban, suburban, and rural).The "neighborhood" variable in this model is ______.

A multiple regression analysis produced the following output from Excel. The correlation coefficient is ____________.

Regression analysis with two dependent variables and two or more independent variables is called multiple regression.

The following ANOVA table is from a multiple regression analysis. Source F p Repression 3 1500 Error 26 Total 2300 The R²value is __________.

In a multiple regression model, the partial regression coefficient of an independent variable represents the increase in the y variable when that independent variable is increased by one unit if the values of all other independent variables are held constant.

In the model y = $\beta$ ₀ + $\beta$ ₁x₁ + $\beta$ ₂x₂ + $\beta$ ₃x₃ + $\varepsilon$ , $\varepsilon$ is a constant.

Introduction to Statistics and Business Analytics

Visualizing Data With Charts and Graphs

Descriptive Statistics

Probability

Discrete Distributions

Continuous Distributions

Sampling and Sampling Distributions

Statistical Inference: Estimation for Single Populations

Statistical Inference: Hypothesis Testing for Single Populations

Statistical Inferences About Two Populations

Analysis of Variance and Design of Experiments

Simple Regression Analysis and Correlation

Building Multiple Regression Models

Time-Series Forecasting and Index Numbers

Analysis of Categorical Data

Nonparametric Statistics

Statistical Quality Control

Decision Analysis

Filters

Exam 13: Multiple Regression Analysis

The following ANOVA table is from a multiple regression analysis. Source F p Repression 3 1500 Error 26 Total 2300 The MSE value is closest to__________.

The following ANOVA table is from a multiple regression analysis. Source F p Repression 3 1500 Error 26 Total 2300 The observed F value is __________.

A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size, household income, and household neighborhood (urban, suburban, and rural).The "neighborhood" variable in this model is ______.

A multiple regression analysis produced the following output from Excel. The correlation coefficient is ____________.

Regression analysis with two dependent variables and two or more independent variables is called multiple regression.

The following ANOVA table is from a multiple regression analysis. Source F p Repression 3 1500 Error 26 Total 2300 The R2 value is __________.

In a multiple regression model, the partial regression coefficient of an independent variable represents the increase in the y variable when that independent variable is increased by one unit if the values of all other independent variables are held constant.

In the model y = β\betaβ 0 + β\betaβ 1x1 + β\betaβ 2x2 + β\betaβ 3x3 + ε\varepsilonε , ε\varepsilonε is a constant.

Introduction to Statistics and Business Analytics

Visualizing Data With Charts and Graphs

Descriptive Statistics

Probability

Discrete Distributions

Continuous Distributions

Sampling and Sampling Distributions

Statistical Inference: Estimation for Single Populations

Statistical Inference: Hypothesis Testing for Single Populations

Statistical Inferences About Two Populations

Analysis of Variance and Design of Experiments

Simple Regression Analysis and Correlation

Building Multiple Regression Models

Time-Series Forecasting and Index Numbers

Analysis of Categorical Data

Nonparametric Statistics

Statistical Quality Control

Decision Analysis

Filters

The following ANOVA table is from a multiple regression analysis. Source F p Repression 3 1500 Error 26 Total 2300 The R²value is __________.

In the model y = $\beta$ ₀ + $\beta$ ₁x₁ + $\beta$ ₂x₂ + $\beta$ ₃x₃ + $\varepsilon$ , $\varepsilon$ is a constant.