Question 1

The model F-statistic is:

Accepted Answer

A) a statistical procedure that estimates regression equation coefficients which produce the lowest sum of squared differences between the actual and predicted values of the dependent variable. 
B) a statistical technique which analyzes the linear relationship between a dependent variable and multiple independent variables by estimating coefficients for the equation for a straight line. 
C) never statistically significant. 
D) a statistic which compares the amount of variation in the dependent measure "explained" or associated with the independent variables to the "unexplained" or error variance. 
E) used in situations where several independent variables are highly correlated with each other. 
A) a statistical procedure that estimates regression equation coefficients which produce the lowest sum of squared differences between the actual and predicted values of the dependent variable. 
B) a statistical technique which analyzes the linear relationship between a dependent variable and multiple independent variables by estimating coefficients for the equation for a straight line. 
C) never statistically significant. 
D) a statistic which compares the amount of variation in the dependent measure "explained" or associated with the independent variables to the "unexplained" or error variance. 
E) used in situations where several independent variables are highly correlated with each other.

Question 2

It is possible for a correlation to be statistically significant and still lack substantive significance.

Accepted Answer

A) True 
 B)False

Question 3

If the coefficient of correlation between two variables is -0.6, their coefficient of determination will be:

Accepted Answer

A) -0.6. 
B) 0.4. 
C) 0.36. 
D) -0.36. 
E) 0.6. 
A) -0.6. 
B) 0.4. 
C) 0.36. 
D) -0.36. 
E) 0.6.

Question 4

The difference between the observed value of the dependent variable and the predicted value of the dependent variable in a regression equation is called the:

Accepted Answer

A) error. 
B) beta weight. 
C) slope. 
D) Y-intercept. 
E) variance. 
A) error. 
B) beta weight. 
C) slope. 
D) Y-intercept. 
E) variance.

Question 5

Under which of the following conditions should one NOT use Pearson correlation coefficient?

Accepted Answer

A) When the researcher wants to determine if two variables have a linear relationship 
B) When the researcher wants to determine if two variables have a curvilinear relationship 
C) When the two variables have been measured using interval scales 
D) When the two variables have been measured using ratio scales 
E) When the two variables come from a bivariate normally distributed populations 
A) When the researcher wants to determine if two variables have a linear relationship 
B) When the researcher wants to determine if two variables have a curvilinear relationship 
C) When the two variables have been measured using interval scales 
D) When the two variables have been measured using ratio scales 
E) When the two variables come from a bivariate normally distributed populations

Question 6

When describing the relationship between variables, researchers have to answer four questions. Which of the following is NOT one of them?

Accepted Answer

A) Is there a relationship between the two variables? 
B) Are the two variables drawn from a normal distribution? 
C) How strong is the relationship? 
D) What is the direction of the relationship? 
E) Is the relationship linear or curvilinear? 
A) Is there a relationship between the two variables? 
B) Are the two variables drawn from a normal distribution? 
C) How strong is the relationship? 
D) What is the direction of the relationship? 
E) Is the relationship linear or curvilinear?

Question 7

Outline the procedure that should be followed in evaluating the results of a regression analysis.

Accepted Answer

a. Assess the statistical significance o

Question 8

When the correlations between independent variables in regression are high enough to cause problems, one approach is to create summated scales consisting of the independent variables that are highly correlated.

Accepted Answer

A) True 
 B)False

Question 9

While studying the relationship between advertising and sales growth, a researcher determines that the relationship is sometimes weak and at other times moderate. This variation from one situation to another is the variation in the _____ of the relationship between advertisement and sales growth.

Accepted Answer

A) strength of association 
B) presence 
C) type 
D) direction 
E) dispersion 
A) strength of association 
B) presence 
C) type 
D) direction 
E) dispersion

Question 10

Given the more complex nature of curvilinear relationships, marketers prefer working with curvilinear rather than linear relationships.

Accepted Answer

A) True 
 B)False

The model F-statistic is:

It is possible for a correlation to be statistically significant and still lack substantive significance.

If the coefficient of correlation between two variables is -0.6, their coefficient of determination will be:

The difference between the observed value of the dependent variable and the predicted value of the dependent variable in a regression equation is called the:

Under which of the following conditions should one NOT use Pearson correlation coefficient?

When describing the relationship between variables, researchers have to answer four questions. Which of the following is NOT one of them?

Outline the procedure that should be followed in evaluating the results of a regression analysis.

When the correlations between independent variables in regression are high enough to cause problems, one approach is to create summated scales consisting of the independent variables that are highly correlated.

While studying the relationship between advertising and sales growth, a researcher determines that the relationship is sometimes weak and at other times moderate. This variation from one situation to another is the variation in the _____ of the relationship between advertisement and sales growth.

Given the more complex nature of curvilinear relationships, marketers prefer working with curvilinear rather than linear relationships.

Marketing Research for Managerial Decision Making

The Marketing Research Process and Proposals

Secondary Data, Literature Reviews, and Hypotheses

Exploratory and Observational Research Designs and Data Collection Approaches

Descriptive and Causal Research Designs

Sampling: Theory and Methods

Measurement and Scaling

Designing the Questionnaire

Qualitative Data Analysis

Preparing Data for Quantitative Analysis

Basic Data Analysis for Quantitative Research

Communicating Marketing Research Findings

Filters

Exam 12: Examining Relationships in Quantitative Research

The model F-statistic is:

It is possible for a correlation to be statistically significant and still lack substantive significance.

If the coefficient of correlation between two variables is -0.6, their coefficient of determination will be:

The difference between the observed value of the dependent variable and the predicted value of the dependent variable in a regression equation is called the:

Under which of the following conditions should one NOT use Pearson correlation coefficient?

When describing the relationship between variables, researchers have to answer four questions. Which of the following is NOT one of them?

Outline the procedure that should be followed in evaluating the results of a regression analysis.

When the correlations between independent variables in regression are high enough to cause problems, one approach is to create summated scales consisting of the independent variables that are highly correlated.

While studying the relationship between advertising and sales growth, a researcher determines that the relationship is sometimes weak and at other times moderate. This variation from one situation to another is the variation in the _____ of the relationship between advertisement and sales growth.

Given the more complex nature of curvilinear relationships, marketers prefer working with curvilinear rather than linear relationships.

Marketing Research for Managerial Decision Making

The Marketing Research Process and Proposals

Secondary Data, Literature Reviews, and Hypotheses

Exploratory and Observational Research Designs and Data Collection Approaches

Descriptive and Causal Research Designs

Sampling: Theory and Methods

Measurement and Scaling

Designing the Questionnaire

Qualitative Data Analysis

Preparing Data for Quantitative Analysis

Basic Data Analysis for Quantitative Research

Communicating Marketing Research Findings

Filters