Question 1

A variable that takes on the values of 0 or 1 and is used to incorporate the effect of qualitative variables in a regression model is called a(n) _____.

Accepted Answer

A)  interaction 
B)  constant variable 
C)  dummy variable 
D)  None of the answers is correct. 
A)  interaction 
B)  constant variable 
C)  dummy variable 
D)  None of the answers is correct.

Question 2

In a multiple regression model, the values of the error term, ε, are assumed to be _____.

Accepted Answer

A)  0 
B)  dependent on each other 
C)  independent of each other 
D)  always negative 
A)  0 
B)  dependent on each other 
C)  independent of each other 
D)  always negative

Question 3

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)  .81 
B)  .11 
C)  .35 
D)  .65 
A)  .81 
B)  .11 
C)  .35 
D)  .65

Question 4

In multiple regression analysis, ______.

Accepted Answer

A)  there can be any number of dependent variables but only one independent variable 
B)  there must be only one independent variable 
C)  the coefficient of determination must be larger than 1 
D)  there can be several independent variables, but only one dependent variable 
A)  there can be any number of dependent variables but only one independent variable 
B)  there must be only one independent variable 
C)  the coefficient of determination must be larger than 1 
D)  there can be several independent variables, but only one dependent variable

Question 5

A regression analysis involved 17 independent variables and 697 observations. The critical value of t for testing the significance of each of the independent variable's coefficients will have _____.

Accepted Answer

A)  696 degrees of freedom 
B)  16 degrees of freedom 
C)  713 degrees of freedom 
D)  714 degrees of freedom 
A)  696 degrees of freedom 
B)  16 degrees of freedom 
C)  713 degrees of freedom 
D)  714 degrees of freedom

Question 6

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 7

A regression model in which more than one independent variable is used to predict the dependent variable is called _____.

Accepted Answer

A)  a simple linear regression model 
B)  a multiple regression model 
C)  an independent model 
D)  None of the answers is correct. 
A)  a simple linear regression model 
B)  a multiple regression model 
C)  an independent model 
D)  None of the answers is correct.

Question 8

In a multiple regression analysis, SSR = 1,000 and SSE = 200. The F statistic for this model is _____.

Accepted Answer

A)  5.0 
B)  1,200 
C)  800 
D)  Not enough information is provided to answer this question. 
A)  5.0 
B)  1,200 
C)  800 
D)  Not enough information is provided to answer this question.

Question 9

In a multiple regression analysis involving 12 independent variables and 166 observations, SSR = 878 and SSE = 122. The coefficient of determination is _____.

Accepted Answer

A)  .1389 
B)  .1220 
C)  .878 
D)  .7317 
A)  .1389 
B)  .1220 
C)  .878 
D)  .7317

Question 10

In a multiple regression model, the error term ε is assumed to _____.

Accepted Answer

A)  have a mean of 1 
B)  have a variance of 0 
C)  have a standard deviation of 1 
D)  be normally distributed 
A)  have a mean of 1 
B)  have a variance of 0 
C)  have a standard deviation of 1 
D)  be normally distributed

Question 11

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)  .80 
B)  .90 
C)  .25 
D)  .15 
A)  .80 
B)  .90 
C)  .25 
D)  .15

Question 12

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 13

In regression analysis, the response variable is the _____.

Accepted Answer

A)  independent variable 
B)  dependent variable 
C)  slope of the regression function 
D)  intercept 
A)  independent variable 
B)  dependent variable 
C)  slope of the regression function 
D)  intercept

Question 14

A variable that cannot be measured in numerical terms is called a _____.

Accepted Answer

A)  non-measurable random variable 
B)  constant variable 
C)  dependent variable 
D)  qualitative variable 
A)  non-measurable random variable 
B)  constant variable 
C)  dependent variable 
D)  qualitative variable

Question 15

The numerical value of the coefficient of determination _____.

Accepted Answer

A)  is always larger than the coefficient of correlation 
B)  is always smaller than the coefficient of correlation 
C)  is negative if the coefficient of determination is negative 
D)  can be larger or smaller than the coefficient of correlation 
A)  is always larger than the coefficient of correlation 
B)  is always smaller than the coefficient of correlation 
C)  is negative if the coefficient of determination is negative 
D)  can be larger or smaller than the coefficient of correlation

Question 16

The adjusted multiple coefficient of determination is adjusted for _____.

Accepted Answer

A)  the number of dependent variables 
B)  the number of independent variables 
C)  the number of equations 
D)  detrimental situations 
A)  the number of dependent variables 
B)  the number of independent variables 
C)  the number of equations 
D)  detrimental situations

Question 17

A measure of goodness of fit for the estimated regression equation is the _____.

Accepted Answer

A)  multiple coefficient of determination 
B)  mean square due to error 
C)  mean square due to regression 
D)  sample size 
A)  multiple coefficient of determination 
B)  mean square due to error 
C)  mean square due to regression 
D)  sample size

Question 18

A multiple regression model has _____.

Accepted Answer

A)  only one independent variable 
B)  more than one dependent variable 
C)  more than one independent variable 
D)  at least two dependent variables 
A)  only one independent variable 
B)  more than one dependent variable 
C)  more than one independent variable 
D)  at least two dependent variables

Question 19

The least squares criterion is _____.

Accepted Answer

A)  min ?(xi - yi)2 
B)  min ?(yi - $\overline{y}$ i)2 
C)  min ?(yi - $\hat { y }$ i)2 
D)  min ?(yi - $\hat { y }$ i) 
A)  min ?(xi - yi)2 
B)  min ?(yi - $\overline{y}$ i)2 
C)  min ?(yi - $\hat { y }$ i)2 
D)  min ?(yi - $\hat { y }$ i)

Question 20

A variable that cannot be measured in terms of how much or how many but instead is assigned values to represent categories is called a(n) _____.

Accepted Answer

A)  interaction 
B)  constant variable 
C)  category variable 
D)  qualitative variable 
A)  interaction 
B)  constant variable 
C)  category variable 
D)  qualitative variable

Exam 15: Multiple Regression

A variable that takes on the values of 0 or 1 and is used to incorporate the effect of qualitative variables in a regression model is called a(n) _____.

In a multiple regression model, the values of the error term, ε, are assumed to be _____.

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

In multiple regression analysis, ______.

A regression analysis involved 17 independent variables and 697 observations. The critical value of t for testing the significance of each of the independent variable's coefficients will have _____.

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 _____.

A regression model in which more than one independent variable is used to predict the dependent variable is called _____.

In a multiple regression analysis, SSR = 1,000 and SSE = 200. The F statistic for this model is _____.

In a multiple regression analysis involving 12 independent variables and 166 observations, SSR = 878 and SSE = 122. The coefficient of determination is _____.

In a multiple regression model, the error term ε is assumed to _____.

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

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 regression analysis, the response variable is the _____.

A variable that cannot be measured in numerical terms is called a _____.

The numerical value of the coefficient of determination _____.

The adjusted multiple coefficient of determination is adjusted for _____.

A measure of goodness of fit for the estimated regression equation is the _____.

A multiple regression model has _____.

The least squares criterion is _____.

A variable that cannot be measured in terms of how much or how many but instead is assigned values to represent categories is called a(n) _____.

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

Regression Analysis: Model Building

Time Series Analysis and Forecasting

Nonparametric Methods

Statistical Methods for Quality Control

Decision Analysis

Sample Survey

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