Question 1

In multiple regression we make a prediction, but we cannot put confidence intervals around our prediction as we can in bivariate regression.

Accepted Answer

A) True 
 B)False  False

Question 2

Multiple regression requires specification of a general conceptual model that identifies independent and dependent variables and shows their expected relationships.

Accepted Answer

A) True 
 B)False  True

Question 3

The weather forecast has called for an 80 percent chance of rain for the last five days and it rained each day. On the sixth day, the forecast again is for an 80 percent chance of rain. Therefore, you forecast that it will rain today. Which method of prediction have you used?

Accepted Answer

A)  guessing 
B)  statistics 
C)  extrapolation 
D)  predictive model 
E)  forecasting 
A)  guessing 
B)  statistics 
C)  extrapolation 
D)  predictive model 
E)  forecasting C

Question 4

If the intercept is found to be 2 and the slope is found to be 5 in a regression result formula, then:

Accepted Answer

A)  y = 2 + 3x 
B)  y = 2 + 5x 
C)  x = 2 + 5y 
D)  x = 2 + 3y 
E)  y = a + 2(5) 
A)  y = 2 + 3x 
B)  y = 2 + 5x 
C)  x = 2 + 5y 
D)  x = 2 + 3y 
E)  y = a + 2(5)

Question 5

In multiple regression analysis, t tests are used to test for the statistical significance of betas. If a beta is insignificant, it means that its respective independent variable plays no meaningful role in predicting the dependent variable, and the independent variable should be "trimmed" from the model.

Accepted Answer

A) True 
 B)False

Question 6

Which of the following SPSS commands allows you to run bivariate regression?

Accepted Answer

A)  ANALYZE; BIVARIATE; REGRESSION 
B)  ANALYZE; REGRESSION; BIVARIATE 
C)  REGRESSION; BIVARIATE 
D)  ANALYZE; REGRESSION; LINEAR 
E)  REGRESSION; BIVARIATE; LINEAR 
A)  ANALYZE; BIVARIATE; REGRESSION 
B)  ANALYZE; REGRESSION; BIVARIATE 
C)  REGRESSION; BIVARIATE 
D)  ANALYZE; REGRESSION; LINEAR 
E)  REGRESSION; BIVARIATE; LINEAR

Question 7

Assume you are developing a general conceptual model for the Advanced Automotive Concepts dataset. Which of the following variables would most likely be your dependent variable?

Accepted Answer

A)  probability of purchasing a particular auto model 
B)  customer income 
C)  customer gender 
D)  customer education 
E)  customer occupation 
A)  probability of purchasing a particular auto model 
B)  customer income 
C)  customer gender 
D)  customer education 
E)  customer occupation

Question 8

In bivariate regression, if the F value is significant (say .05 or less), then:

Accepted Answer

A)  we accept the null hypothesis that a straight-line model fits our data 
B)  we reject the null hypothesis that a straight-line model does not fit our data 
C)  we abandon our efforts to analyze the two variables 
D)  we check for outliers 
E)  we rerun the regression 
A)  we accept the null hypothesis that a straight-line model fits our data 
B)  we reject the null hypothesis that a straight-line model does not fit our data 
C)  we abandon our efforts to analyze the two variables 
D)  we check for outliers 
E)  we rerun the regression

Question 9

Which of the following is NOT true of prediction?

Accepted Answer

A)  It is a statement of what is believed will happen in the future. 
B)  It may be based on prior observation. 
C)  We are seldom confronted with the need to make predictions. 
D)  It may be based on past experience. 
E)  Marketing managers are constantly faced with the need to make predictions. 
A)  It is a statement of what is believed will happen in the future. 
B)  It may be based on prior observation. 
C)  We are seldom confronted with the need to make predictions. 
D)  It may be based on past experience. 
E)  Marketing managers are constantly faced with the need to make predictions.

Question 10

Which sequence of SPSS commands would you select in order to run stepwise multiple regression?

Accepted Answer

A)  ANALYZE; REGRESSION; LINEARSTEPS 
B)  ANALYZE; REGRESSION; LINEAR; METHOD; STEPWISE 
C)  STEPWISE; LINEAR REGRESSION; GO 
D)  STEPWISE; LINEAR REGRESSION 
E)  ANALYZE; REGRESSION; METHOD; STEP 
A)  ANALYZE; REGRESSION; LINEARSTEPS 
B)  ANALYZE; REGRESSION; LINEAR; METHOD; STEPWISE 
C)  STEPWISE; LINEAR REGRESSION; GO 
D)  STEPWISE; LINEAR REGRESSION 
E)  ANALYZE; REGRESSION; METHOD; STEP

Question 11

Bivariate regression analysis is defined as a predictive analysis technique in which:

Accepted Answer

A)  a pattern is identified over time and projected into the future 
B)  a relationship that exists across time is observed to make a prediction 
C)  one variable is used to predict the level of another by use of the straight-line formula 
D)  one variable is used to predict the level of another by use of a scatter diagram 
E)  a relationship that exists at one point in time is observed to make a prediction 
A)  a pattern is identified over time and projected into the future 
B)  a relationship that exists across time is observed to make a prediction 
C)  one variable is used to predict the level of another by use of the straight-line formula 
D)  one variable is used to predict the level of another by use of a scatter diagram 
E)  a relationship that exists at one point in time is observed to make a prediction

Question 12

A regression plane is the shape of the independent variable in multiple regression analysis.

Accepted Answer

A) True 
 B)False

Question 13

In multiple regression, you must test for the significance of the betas for each of the independent variables. You would do this by looking for:

Accepted Answer

A)  a significant t test for each independent variable 
B)  a significant ANOVA for each independent variable 
C)  a significant alpha level for each independent variable 
D)  a significant non-linear beta weight for each independent variable 
E)  a significant R for each independent variable 
A)  a significant t test for each independent variable 
B)  a significant ANOVA for each independent variable 
C)  a significant alpha level for each independent variable 
D)  a significant non-linear beta weight for each independent variable 
E)  a significant R for each independent variable

Question 14

If we wanted to use a type of regression that first enters the variable that explains the most variance, then the variable that explains the second highest level of variance and so on, we would use "ordinal regression."

Accepted Answer

A) True 
 B)False

Question 15

The R Square value is very important because it tells us how well our regression line fits the scatter of data points. It may range from 0 to +1.00 because it is the square of the correlation coefficient, which may range from -1.00 to +1.00.

Accepted Answer

A) True 
 B)False

Question 16

We must use standardized beta weights to compare the size of beta weights in multiple regression because the independent variables they represent are often measured with different units.

Accepted Answer

A) True 
 B)False

Question 17

A form of regression analysis where more than one independent variable is used in the regression equation is known as:

Accepted Answer

A)  regression planes 
B)  additivity 
C)  multiple regression analysis 
D)  independence assumption 
E)  MANOVA 
A)  regression planes 
B)  additivity 
C)  multiple regression analysis 
D)  independence assumption 
E)  MANOVA

Question 18

A measure of the accuracy of the predictions of the regression equation is referred to as:

Accepted Answer

A)  standard error of the mean 
B)  standard deviation 
C)  residuals deviation 
D)  standard error of the estimate 
E)  regression deviation 
A)  standard error of the mean 
B)  standard deviation 
C)  residuals deviation 
D)  standard error of the estimate 
E)  regression deviation

Question 19

In using extrapolation, the forecaster goes beyond what happened "yesterday" and identifies relationships between a number of variables such as the relationship between winds and barometric pressure.

Accepted Answer

A) True 
 B)False

Question 20

VIF is an acronym for "Very InFrequent."

Accepted Answer

A) True 
 B)False

In multiple regression we make a prediction, but we cannot put confidence intervals around our prediction as we can in bivariate regression.

Multiple regression requires specification of a general conceptual model that identifies independent and dependent variables and shows their expected relationships.

The weather forecast has called for an 80 percent chance of rain for the last five days and it rained each day. On the sixth day, the forecast again is for an 80 percent chance of rain. Therefore, you forecast that it will rain today. Which method of prediction have you used?

If the intercept is found to be 2 and the slope is found to be 5 in a regression result formula, then:

Which of the following SPSS commands allows you to run bivariate regression?

Assume you are developing a general conceptual model for the Advanced Automotive Concepts dataset. Which of the following variables would most likely be your dependent variable?

In bivariate regression, if the F value is significant (say .05 or less), then:

Which of the following is NOT true of prediction?

Which sequence of SPSS commands would you select in order to run stepwise multiple regression?

Bivariate regression analysis is defined as a predictive analysis technique in which:

A regression plane is the shape of the independent variable in multiple regression analysis.

In multiple regression, you must test for the significance of the betas for each of the independent variables. You would do this by looking for:

If we wanted to use a type of regression that first enters the variable that explains the most variance, then the variable that explains the second highest level of variance and so on, we would use "ordinal regression."

The R Square value is very important because it tells us how well our regression line fits the scatter of data points. It may range from 0 to +1.00 because it is the square of the correlation coefficient, which may range from -1.00 to +1.00.

We must use standardized beta weights to compare the size of beta weights in multiple regression because the independent variables they represent are often measured with different units.

A form of regression analysis where more than one independent variable is used in the regression equation is known as:

A measure of the accuracy of the predictions of the regression equation is referred to as:

In using extrapolation, the forecaster goes beyond what happened "yesterday" and identifies relationships between a number of variables such as the relationship between winds and barometric pressure.

VIF is an acronym for "Very InFrequent."

Introduction to Marketing Research

The Marketing Research Process

The Marketing Research Industry

Defining the Problem and Determining Research Objectives

Research Design

Using Secondary Data and Online Information Databases

Standardized Information Sources

Observation, Focus Groups, and Other Qualitative Methods

Survey Data-Collection Methods

Measurement in Marketing Research

Designing the Questionnaire

Determining How to Select the Sample

Determining the Size of a Sample

Data Collection in the Field, Nonresponse Error, and Questionnaire Screening

Basic Data Analysis: Descriptive Statistics

Generalizing a Sample's Findings to its Population and Testing Hypotheses About Percents and Means

Testing for Differences Between Two Groups or Among More Than

Determining and Interpreting Associations Among Variables

The Marketing Research Report: Preparation and Presentation

Filters

Exam 19: Regression Analysis in Marketing Research

In multiple regression we make a prediction, but we cannot put confidence intervals around our prediction as we can in bivariate regression.

Multiple regression requires specification of a general conceptual model that identifies independent and dependent variables and shows their expected relationships.

The weather forecast has called for an 80 percent chance of rain for the last five days and it rained each day. On the sixth day, the forecast again is for an 80 percent chance of rain. Therefore, you forecast that it will rain today. Which method of prediction have you used?

If the intercept is found to be 2 and the slope is found to be 5 in a regression result formula, then:

Which of the following SPSS commands allows you to run bivariate regression?

Assume you are developing a general conceptual model for the Advanced Automotive Concepts dataset. Which of the following variables would most likely be your dependent variable?

In bivariate regression, if the F value is significant (say .05 or less), then:

Which of the following is NOT true of prediction?

Which sequence of SPSS commands would you select in order to run stepwise multiple regression?

Bivariate regression analysis is defined as a predictive analysis technique in which:

A regression plane is the shape of the independent variable in multiple regression analysis.

In multiple regression, you must test for the significance of the betas for each of the independent variables. You would do this by looking for:

If we wanted to use a type of regression that first enters the variable that explains the most variance, then the variable that explains the second highest level of variance and so on, we would use "ordinal regression."

The R Square value is very important because it tells us how well our regression line fits the scatter of data points. It may range from 0 to +1.00 because it is the square of the correlation coefficient, which may range from -1.00 to +1.00.

We must use standardized beta weights to compare the size of beta weights in multiple regression because the independent variables they represent are often measured with different units.

A form of regression analysis where more than one independent variable is used in the regression equation is known as:

A measure of the accuracy of the predictions of the regression equation is referred to as:

In using extrapolation, the forecaster goes beyond what happened "yesterday" and identifies relationships between a number of variables such as the relationship between winds and barometric pressure.

VIF is an acronym for "Very InFrequent."

Introduction to Marketing Research

The Marketing Research Process

The Marketing Research Industry

Defining the Problem and Determining Research Objectives

Research Design

Using Secondary Data and Online Information Databases

Standardized Information Sources

Observation, Focus Groups, and Other Qualitative Methods

Survey Data-Collection Methods

Measurement in Marketing Research

Designing the Questionnaire

Determining How to Select the Sample

Determining the Size of a Sample

Data Collection in the Field, Nonresponse Error, and Questionnaire Screening

Basic Data Analysis: Descriptive Statistics

Generalizing a Sample's Findings to its Population and Testing Hypotheses About Percents and Means

Testing for Differences Between Two Groups or Among More Than

Determining and Interpreting Associations Among Variables

The Marketing Research Report: Preparation and Presentation

Filters