Question 1

________ helps the researcher to understand whether observed data is truly linear and whether the data is a good fit to the model being used.

Accepted Answer

A) Analysis of prediction 
B) Control data 
C) Analysis of residuals 
D) Analysis of variance 
E) Values comparison 
A) Analysis of prediction 
B) Control data 
C) Analysis of residuals 
D) Analysis of variance 
E) Values comparison

Question 2

A standardized beta coefficient is defined as:

Accepted Answer

A) the result of adding the difference between each independent variable value and its mean and the standard deviation of that independent variable. 
B) the result of multiplying the difference between each independent variable value and its mean by the standard deviation of that independent variable. 
C) the result of dividing the standard deviation of an independent variable by the difference between that independent variable value and its mean. 
D) the result of dividing the difference between each independent variable value and its mean by the standard deviation of that independent variable. 
E) the result of subtracting the difference between each independent variable value and its mean by the standard deviation of that independent variable. 
A) the result of adding the difference between each independent variable value and its mean and the standard deviation of that independent variable. 
B) the result of multiplying the difference between each independent variable value and its mean by the standard deviation of that independent variable. 
C) the result of dividing the standard deviation of an independent variable by the difference between that independent variable value and its mean. 
D) the result of dividing the difference between each independent variable value and its mean by the standard deviation of that independent variable. 
E) the result of subtracting the difference between each independent variable value and its mean by the standard deviation of that independent variable.

Question 3

We can sometimes improve a regression analysis finding by removing outliers and rerunning the regression analysis.

Accepted Answer

A) True 
 B)False

Question 4

In multiple regression,the presence of correlations among the independent variables is termed:

Accepted Answer

A) independence assumption. 
B) multicollinearity. 
C) additivity. 
D) regression plane. 
E) multicorrelation. 
A) independence assumption. 
B) multicollinearity. 
C) additivity. 
D) regression plane. 
E) multicorrelation.

Question 5

Which of the following in multiple regression is a handy measure of the strength of the overall relationship?

Accepted Answer

A) Adjusted R 
B) Multiple R 
C) multicollinearity 
D) VIF 
E) Adjusted B 
A) Adjusted R 
B) Multiple R 
C) multicollinearity 
D) VIF 
E) Adjusted B

Question 6

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 7

The main purpose of ANOVA in bivariate regression is to:

Accepted Answer

A) tell us if there are significant differences between three or more means. 
B) tell us if ANOVA is an issue. 
C) tell us if the straight-line model fits the data we are analyzing. 
D) provide a frequency table for further analysis. 
E) None of the above;ANOVA is not used in regression. 
A) tell us if there are significant differences between three or more means. 
B) tell us if ANOVA is an issue. 
C) tell us if the straight-line model fits the data we are analyzing. 
D) provide a frequency table for further analysis. 
E) None of the above;ANOVA is not used in regression.

Question 8

________ is a simple technique for analyzing two variables to predict behavior or activity in the marketplace.

Accepted Answer

A) Regression analysis 
B) Variance analysis 
C) Bivariate regression 
D) Multiple regression 
E) Stepwise regression 
A) Regression analysis 
B) Variance analysis 
C) Bivariate regression 
D) Multiple regression 
E) Stepwise regression

Question 9

VIF is an acronym for "Very InFrequent."

Accepted Answer

A) True 
 B)False

Question 10

You run bivariate regression analysis and you find that the ANOVA results indicate that you have Sig.value for your F of .05.Now,looking under your Coefficients output,you have an intercept value and a slope value.You should use these values only when:

Accepted Answer

A) they are both significant,i.e. ,have Sig.values above 1.00. 
B) they are both significant,i.e. ,have Sig.values below 1.00. 
C) they are both significant,i.e. ,have Sig.values equal to or below .05. 
D) at least one is significant,i.e. ,has a Sig.value above .80. 
E) None of the above;because the F value in the ANOVA was not significant,you should not have even looked at the Coefficients output. 
A) they are both significant,i.e. ,have Sig.values above 1.00. 
B) they are both significant,i.e. ,have Sig.values below 1.00. 
C) they are both significant,i.e. ,have Sig.values equal to or below .05. 
D) at least one is significant,i.e. ,has a Sig.value above .80. 
E) None of the above;because the F value in the ANOVA was not significant,you should not have even looked at the Coefficients output.

Question 11

In the following straight-line formula,y = a + bx,the variable being predicted is the beta weight,b.

Accepted Answer

A) True 
 B)False

Question 12

When a researcher uses gender as a dummy variable in a study for a client,it is important not to distort the findings by highlighting this fact in the final report and presentation.

Accepted Answer

A) True 
 B)False

Question 13

Multiple regression may be used as a screening device in the sense that it may be used to reduce large numbers of potential independent variables in order to spot those that are most salient for the dependent variable.

Accepted Answer

A) True 
 B)False

Question 14

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 15

In evaluating your bivariate regression analysis findings,you first determine whether or not a linear relationship between the independent and dependent variable exists in the population and secondly you:

Accepted Answer

A) determine the significance of the intercept and the slope. 
B) determine the significance of the covariation. 
C) determine if the two variables vary together. 
D) determine if the two variables belong in the same regression matrix. 
E) determine if the two variables predict the intercept and the slope. 
A) determine the significance of the intercept and the slope. 
B) determine the significance of the covariation. 
C) determine if the two variables vary together. 
D) determine if the two variables belong in the same regression matrix. 
E) determine if the two variables predict the intercept and the slope.

Question 16

In the formula for a straight line,the intercept is known as:

Accepted Answer

A) the dependent variable. 
B) the variable used to predict the dependent variable. 
C) the change in y for any unit change in x. 
D) the point where the line cuts the y axis when x = 0. 
E) b 
A) the dependent variable. 
B) the variable used to predict the dependent variable. 
C) the change in y for any unit change in x. 
D) the point where the line cuts the y axis when x = 0. 
E) b

Question 17

Which of the following residuals shows an exact prediction?

Accepted Answer

A) 0 
B) +1.0 
C) -25 
D) +25 
E) 100.0 
A) 0 
B) +1.0 
C) -25 
D) +25 
E) 100.0

Question 18

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 19

A graph of the dependent variable in multiple regression analysis is referred to as:

Accepted Answer

A) confidence intervals. 
B) multiple regression. 
C) multiple scatter plots. 
D) regression plane. 
E) a multi-scatter plot. 
A) confidence intervals. 
B) multiple regression. 
C) multiple scatter plots. 
D) regression plane. 
E) a multi-scatter plot.

Question 20

The SPSS command for running multiple regression is: ANALYZE;REGRESSION;LINEAR.

Accepted Answer

A) True 
 B)False

________ helps the researcher to understand whether observed data is truly linear and whether the data is a good fit to the model being used.

A standardized beta coefficient is defined as:

We can sometimes improve a regression analysis finding by removing outliers and rerunning the regression analysis.

In multiple regression,the presence of correlations among the independent variables is termed:

Which of the following in multiple regression is a handy measure of the strength of the overall relationship?

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.

The main purpose of ANOVA in bivariate regression is to:

________ is a simple technique for analyzing two variables to predict behavior or activity in the marketplace.

VIF is an acronym for "Very InFrequent."

You run bivariate regression analysis and you find that the ANOVA results indicate that you have Sig.value for your F of .05.Now,looking under your Coefficients output,you have an intercept value and a slope value.You should use these values only when:

In the following straight-line formula,y = a + bx,the variable being predicted is the beta weight,b.

When a researcher uses gender as a dummy variable in a study for a client,it is important not to distort the findings by highlighting this fact in the final report and presentation.

Multiple regression may be used as a screening device in the sense that it may be used to reduce large numbers of potential independent variables in order to spot those that are most salient for the dependent variable.

In evaluating your bivariate regression analysis findings,you first determine whether or not a linear relationship between the independent and dependent variable exists in the population and secondly you:

In the formula for a straight line,the intercept is known as:

Which of the following residuals shows an exact prediction?

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 graph of the dependent variable in multiple regression analysis is referred to as:

The SPSS command for running multiple regression is: ANALYZE;REGRESSION;LINEAR.

Introduction to Marketing Research

The Marketing Research Industry

The Marketing Research Process Defining the Problem and Research Objectives

Research Design

Secondary Data Packaged Information

Utilizing Exploratory and Qualitative Research Techniques

Evaluating Survey Data Collection Methods

Understanding Measurement, developing Questions, and Designing the Questionnaire

Selecting the Sample

Determining the Size of a Sample

Dealing With Fieldwork and Data Quality

Using Basic Descriptive Analysis, performing Population Estimates, and Testing Hypotheses

Implementing Basic Differences Tests

Making Use of Associations Tests

Writing the Research Report

Filters

Exam 15: Understanding Regression Analysis Basics

________ helps the researcher to understand whether observed data is truly linear and whether the data is a good fit to the model being used.

A standardized beta coefficient is defined as:

We can sometimes improve a regression analysis finding by removing outliers and rerunning the regression analysis.

In multiple regression,the presence of correlations among the independent variables is termed:

Which of the following in multiple regression is a handy measure of the strength of the overall relationship?

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.

The main purpose of ANOVA in bivariate regression is to:

________ is a simple technique for analyzing two variables to predict behavior or activity in the marketplace.

VIF is an acronym for "Very InFrequent."

You run bivariate regression analysis and you find that the ANOVA results indicate that you have Sig.value for your F of .05.Now,looking under your Coefficients output,you have an intercept value and a slope value.You should use these values only when:

In the following straight-line formula,y = a + bx,the variable being predicted is the beta weight,b.

When a researcher uses gender as a dummy variable in a study for a client,it is important not to distort the findings by highlighting this fact in the final report and presentation.

Multiple regression may be used as a screening device in the sense that it may be used to reduce large numbers of potential independent variables in order to spot those that are most salient for the dependent variable.

In evaluating your bivariate regression analysis findings,you first determine whether or not a linear relationship between the independent and dependent variable exists in the population and secondly you:

In the formula for a straight line,the intercept is known as:

Which of the following residuals shows an exact prediction?

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 graph of the dependent variable in multiple regression analysis is referred to as:

The SPSS command for running multiple regression is: ANALYZE;REGRESSION;LINEAR.

Introduction to Marketing Research

The Marketing Research Industry

The Marketing Research Process Defining the Problem and Research Objectives

Research Design

Secondary Data Packaged Information

Utilizing Exploratory and Qualitative Research Techniques

Evaluating Survey Data Collection Methods

Understanding Measurement, developing Questions, and Designing the Questionnaire

Selecting the Sample

Determining the Size of a Sample

Dealing With Fieldwork and Data Quality

Using Basic Descriptive Analysis, performing Population Estimates, and Testing Hypotheses

Implementing Basic Differences Tests

Making Use of Associations Tests

Writing the Research Report

Filters