Question 1

Use of the Pearson correlation coefficient assumes the variables have a normally distributed population.

Accepted Answer

A) True 
 B)False

Question 2

When knowledge about the behavior of one variable allows you to predict the behavior of another variable, this is another way of studying the _____ of the relationship.

Accepted Answer

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

Question 3

For a retail store, there exists a strong relationship between the amount spent on local television advertising and store sales. As it increases advertising expenditure, sales go up. Which of the following seems to be the most appropriate Pearson correlation coefficient for this relationship?

Accepted Answer

A) 0.01 
B) 0.05 
C) 0.90 
D) -0.50 
E) 99.1 
A) 0.01 
B) 0.05 
C) 0.90 
D) -0.50 
E) 99.1

Question 4

When the correlation coefficient is weak, the researcher must consider two possibilities:

Accepted Answer

A) there simply is no consistent, systematic relationship between the two items in the population and the association exists, but it is not linear and must be investigated further. 
B) there is a consistent, systematic relationship between the two items in the population, but it is not linear and must be investigated further. 
C) there simply is no consistent, systematic relationship between the two items in the population and the association exists, but it is linear and must be investigated further. 
D) there simply is no consistent, systematic relationship between the two items in the population and the association exists, but it is linear and does not need be investigated further. 
E) there is a consistent, systematic relationship between the two items in the population, but it is linear and must be investigated further. 
A) there simply is no consistent, systematic relationship between the two items in the population and the association exists, but it is not linear and must be investigated further. 
B) there is a consistent, systematic relationship between the two items in the population, but it is not linear and must be investigated further. 
C) there simply is no consistent, systematic relationship between the two items in the population and the association exists, but it is linear and must be investigated further. 
D) there simply is no consistent, systematic relationship between the two items in the population and the association exists, but it is linear and does not need be investigated further. 
E) there is a consistent, systematic relationship between the two items in the population, but it is linear and must be investigated further.

Question 5

Multicollinearity 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) an estimated regression coefficient which has been recalculated to have a mean of zero and a standard deviation of 1. 
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) a situation in which 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) an estimated regression coefficient which has been recalculated to have a mean of zero and a standard deviation of 1. 
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) a situation in which several independent variables are highly correlated with each other.

Question 6

Discuss the problem of multicollinearity encountered in multiple regression analysis.

Accepted Answer

The problem of multicollinearity occurs

Question 7

A problem area for marketing researchers in multiple regression is when the independent variables are highly correlated among themselves.

Accepted Answer

A) True 
 B)False

Question 8

In a bivariate regression analysis, there is / are _____ predictor variable(s).

Accepted Answer

A) 0 
B) 1 
C) 2 
D) 3 
E) 4 
A) 0 
B) 1 
C) 2 
D) 3 
E) 4

Question 9

Is it possible to establish through a regression analysis if a variable is a dependent or an independent variable?

Accepted Answer

While there is a convention of calling v

Question 10

Independent variables are also called predictor variables.

Accepted Answer

A) True 
 B)False

Question 11

A positive relationship between X and Y means that increases in X are associated with decreases in Y.

Accepted Answer

A) True 
 B)False

Question 12

Once the statistical significance of the regression coefficients is determined, which of the following questions would be answered?

Accepted Answer

A) How strong is the relationship? 
B) Is there a relationship between the independent and dependent variables? 
C) Is the regression coefficient significant? 
D) Is the slope of the regression line significant? 
E) Is the error term of the equation significant? 
A) How strong is the relationship? 
B) Is there a relationship between the independent and dependent variables? 
C) Is the regression coefficient significant? 
D) Is the slope of the regression line significant? 
E) Is the error term of the equation significant?

Question 13

A researcher finds that the correlation coefficient between two variables is 0.20. She wants to know if this level of correlation is meaningful from a managerial perspective or not. She is interested in determining the _____ of her results.

Accepted Answer

A) statistical significance 
B) determination significance 
C) linearity significance 
D) substantive significance 
E) absolute significance 
A) statistical significance 
B) determination significance 
C) linearity significance 
D) substantive significance 
E) absolute significance

Question 14

Covariation refers to the direction of the relationship between two variables.

Accepted Answer

A) True 
 B)False

Question 15

The coefficient of determination:

Accepted Answer

A) describes the variation in the dependent variable described by the control variable. 
B) tells you the percent of the total variation in the independent variable explained by the dependent variable. 
C) ranges from -1.0 to + 1.0. 
D) ranges from zero to + 1.0. 
E) is a stronger measure than the Pearson correlation coefficient. 
A) describes the variation in the dependent variable described by the control variable. 
B) tells you the percent of the total variation in the independent variable explained by the dependent variable. 
C) ranges from -1.0 to + 1.0. 
D) ranges from zero to + 1.0. 
E) is a stronger measure than the Pearson correlation coefficient.

Question 16

The strength of association is determined by the size of the correlation coefficient.

Accepted Answer

A) True 
 B)False

Question 17

In bivariate regression analysis, a researcher tries to generate the best-filling line called the regression line. Any point that doesn't fall on this line contributes to error. The total error in regression is determined by:

Accepted Answer

A) the number of points that don't fall on the regression line. 
B) the proportion of points that don't fall on the regression line. 
C) the sum of distances between the regression line and the points not on the line. 
D) the square of the sum of distances between the regression line and the points not on the line. 
E) the percentage of points that don't fall on the regression line. 
A) the number of points that don't fall on the regression line. 
B) the proportion of points that don't fall on the regression line. 
C) the sum of distances between the regression line and the points not on the line. 
D) the square of the sum of distances between the regression line and the points not on the line. 
E) the percentage of points that don't fall on the regression line.

Question 18

The null hypothesis for Pearson's correlation coefficient states there is an association between the two variables in the population and that the correlation coefficient is one.

Accepted Answer

A) True 
 B)False

Question 19

Explain the concept of covariation.

Accepted Answer

Covariation describes the rela

Question 20

If a researcher is interested in measuring the effect of two independent variables on a dependent variable, he / she should use:

Accepted Answer

A) pearson correlation coefficient. 
B) spearman correlation coefficient. 
C) bivariate regression analysis. 
D) multiple regression analysis. 
E) simple regression. 
A) pearson correlation coefficient. 
B) spearman correlation coefficient. 
C) bivariate regression analysis. 
D) multiple regression analysis. 
E) simple regression.

Use of the Pearson correlation coefficient assumes the variables have a normally distributed population.

When knowledge about the behavior of one variable allows you to predict the behavior of another variable, this is another way of studying the _____ of the relationship.

For a retail store, there exists a strong relationship between the amount spent on local television advertising and store sales. As it increases advertising expenditure, sales go up. Which of the following seems to be the most appropriate Pearson correlation coefficient for this relationship?

When the correlation coefficient is weak, the researcher must consider two possibilities:

Multicollinearity is:

Discuss the problem of multicollinearity encountered in multiple regression analysis.

A problem area for marketing researchers in multiple regression is when the independent variables are highly correlated among themselves.

In a bivariate regression analysis, there is / are _____ predictor variable(s).

Is it possible to establish through a regression analysis if a variable is a dependent or an independent variable?

Independent variables are also called predictor variables.

A positive relationship between X and Y means that increases in X are associated with decreases in Y.

Once the statistical significance of the regression coefficients is determined, which of the following questions would be answered?

A researcher finds that the correlation coefficient between two variables is 0.20. She wants to know if this level of correlation is meaningful from a managerial perspective or not. She is interested in determining the _____ of her results.

Covariation refers to the direction of the relationship between two variables.

The coefficient of determination:

The strength of association is determined by the size of the correlation coefficient.

In bivariate regression analysis, a researcher tries to generate the best-filling line called the regression line. Any point that doesn't fall on this line contributes to error. The total error in regression is determined by:

The null hypothesis for Pearson's correlation coefficient states there is an association between the two variables in the population and that the correlation coefficient is one.

Explain the concept of covariation.

If a researcher is interested in measuring the effect of two independent variables on a dependent variable, he / she should use:

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

Use of the Pearson correlation coefficient assumes the variables have a normally distributed population.

When knowledge about the behavior of one variable allows you to predict the behavior of another variable, this is another way of studying the _____ of the relationship.

For a retail store, there exists a strong relationship between the amount spent on local television advertising and store sales. As it increases advertising expenditure, sales go up. Which of the following seems to be the most appropriate Pearson correlation coefficient for this relationship?

When the correlation coefficient is weak, the researcher must consider two possibilities:

Multicollinearity is:

Discuss the problem of multicollinearity encountered in multiple regression analysis.

A problem area for marketing researchers in multiple regression is when the independent variables are highly correlated among themselves.

In a bivariate regression analysis, there is / are _____ predictor variable(s).

Is it possible to establish through a regression analysis if a variable is a dependent or an independent variable?

Independent variables are also called predictor variables.

A positive relationship between X and Y means that increases in X are associated with decreases in Y.

Once the statistical significance of the regression coefficients is determined, which of the following questions would be answered?

A researcher finds that the correlation coefficient between two variables is 0.20. She wants to know if this level of correlation is meaningful from a managerial perspective or not. She is interested in determining the _____ of her results.

Covariation refers to the direction of the relationship between two variables.

The coefficient of determination:

The strength of association is determined by the size of the correlation coefficient.

In bivariate regression analysis, a researcher tries to generate the best-filling line called the regression line. Any point that doesn't fall on this line contributes to error. The total error in regression is determined by:

The null hypothesis for Pearson's correlation coefficient states there is an association between the two variables in the population and that the correlation coefficient is one.

Explain the concept of covariation.

If a researcher is interested in measuring the effect of two independent variables on a dependent variable, he / she should use:

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