Question 1

In bivariate regression analysis, the procedure used to determine the best fitting line is called the:

Accepted Answer

A) least squares procedure. 
B) squared error procedure. 
C) sum of errors procedure. 
D) least error procedure. 
E) minimum error procedure. 
A) least squares procedure. 
B) squared error procedure. 
C) sum of errors procedure. 
D) least error procedure. 
E) minimum error procedure. A

Question 2

If the correlation coefficient is between 0.0 and 0.2, then there is a good chance the null hypothesis will be rejected.

Accepted Answer

A) True 
 B)False  False

Question 3

Discuss the relationship between the Pearson correlation coefficient and the coefficient of determination.

Accepted Answer

Pearson correlation coefficient is a measure of the strength of a linear relationship between two metric variables. The coefficient of determination is obtained by squaring the correlation coefficient. It is a measure of the amount of variation in one variable accounted for by the other variable.

Question 4

A scatter plot wherein the dots form an ellipse can be described as a positive relationship.

Accepted Answer

A) True 
 B)False

Question 5

In a regression analysis, the horizontal distance between the estimated regression line and the actual data points is the unexplained variance called error.

Accepted Answer

A) True 
 B)False

Question 6

A researcher writes the general formula for a straight line. In this formula, the dependent variable is sales and the independent variable is advertising expenditure. In this formula, the amount of sales that will be realized when the advertising expenditure is zero, is represented by the symbol:

Accepted Answer

A) Y. 
B) a. 
C) b. 
D) X. 
E) e. 
A) Y. 
B) a. 
C) b. 
D) X. 
E) e.

Question 7

A researcher plots a scatter diagram of two variables. The dots on the plot are scattered roughly as a circle. This indicates that the relationship (covariation) between the two variables is:

Accepted Answer

A) linear, positive. 
B) linear, negative. 
C) circular, positive. 
D) circular, negative. 
E) very close to zero. 
A) linear, positive. 
B) linear, negative. 
C) circular, positive. 
D) circular, negative. 
E) very close to zero.

Question 8

"As the ownership of DVD players goes up, DVD rentals at Blockbuster will also go up." This statement illustrates the concept of:

Accepted Answer

A) co-dependence. 
B) co-alteration. 
C) covariation. 
D) co-existence. 
E) convergence. 
A) co-dependence. 
B) co-alteration. 
C) covariation. 
D) co-existence. 
E) convergence.

Question 9

In a regression analysis, the strength of the relationship between the independent and dependent variables is indicated by:

Accepted Answer

A) the regression coefficient. 
B) the rS1U1P12S1S1P0. 
C) the significance level. 
D) the t statistic. 
E) the beta coefficient. 
A) the regression coefficient. 
B) the rS1U1P12S1S1P0. 
C) the significance level. 
D) the t statistic. 
E) the beta coefficient.

Question 10

For a given sample, which of the following correlation coefficients is most likely to be found statistically significant?

Accepted Answer

A) 0.01 
B) 0.05 
C) 0.10 
D) 0.50 
E) 0.90 
A) 0.01 
B) 0.05 
C) 0.10 
D) 0.50 
E) 0.90

Question 11

Which of the following statements is false regarding the beta coefficient?

Accepted Answer

A) It is the standardized regression coefficient. 
B) It shows the change in the dependent variable for each unit change in the independent variable. 
C) It removes the effects of using different scales of measurement. 
D) It ranges from .00 to 1.00, and can be either positive or negative. 
E) A negative beta means as the size of the independent variable decreases then the size of the dependent variable gets smaller. 
A) It is the standardized regression coefficient. 
B) It shows the change in the dependent variable for each unit change in the independent variable. 
C) It removes the effects of using different scales of measurement. 
D) It ranges from .00 to 1.00, and can be either positive or negative. 
E) A negative beta means as the size of the independent variable decreases then the size of the dependent variable gets smaller.

Question 12

When the correlation coefficient is weak, it is possible that an association exists but it is not linear.

Accepted Answer

A) True 
 B)False

Question 13

The statistical procedure that results in predictions with the lowest sum of squared differences between actual and predicted values in a regression equation is called:

Accepted Answer

A) SPSS. 
B) unexplained variance. 
C) ordinary least squares. 
D) the slope. 
E) regression coefficient. 
A) SPSS. 
B) unexplained variance. 
C) ordinary least squares. 
D) the slope. 
E) regression coefficient.

Question 14

Regression analysis assumes there is a straight line relationship between the independent and dependent variables.

Accepted Answer

A) True 
 B)False

Question 15

r S1U1P12S1S1P0 describes the amount of variation in the dependent variable that is associated with the variation in the independent variable.

Accepted Answer

A) True 
 B)False

Question 16

The least squares procedure determines the best-fitting line by minimizing the vertical distances of all the data points from the line.

Accepted Answer

A) True 
 B)False

Question 17

In multiple regression, the value of beta coefficient can never be greater than 1.

Accepted Answer

A) True 
 B)False

Question 18

A researcher wants to measure the degree of association between two variables, education and product knowledge. Education is measured by asking respondents to choose from one of the four options: less than high school, high school, some college, college graduate. Product knowledge is measured by asking respondents to pick from one of the three options: no knowledge, some knowledge, very knowledgeable. Given this information, which of the following measures would be appropriate?

Accepted Answer

A) Chi-square test 
B) Pearson correlation coefficient 
C) Coefficient of determination 
D) Spearman rank-order correlation coefficient 
E) Scatter plot 
A) Chi-square test 
B) Pearson correlation coefficient 
C) Coefficient of determination 
D) Spearman rank-order correlation coefficient 
E) Scatter plot

Question 19

In the formula Y = a + bX + eS1U1B1iS1U1B0, Y is the dependent variable.

Accepted Answer

A) True 
 B)False

Question 20

Bivariate regression has only one independent variable.

Accepted Answer

A) True 
 B)False

In bivariate regression analysis, the procedure used to determine the best fitting line is called the:

If the correlation coefficient is between 0.0 and 0.2, then there is a good chance the null hypothesis will be rejected.

Discuss the relationship between the Pearson correlation coefficient and the coefficient of determination.

A scatter plot wherein the dots form an ellipse can be described as a positive relationship.

In a regression analysis, the horizontal distance between the estimated regression line and the actual data points is the unexplained variance called error.

A researcher writes the general formula for a straight line. In this formula, the dependent variable is sales and the independent variable is advertising expenditure. In this formula, the amount of sales that will be realized when the advertising expenditure is zero, is represented by the symbol:

A researcher plots a scatter diagram of two variables. The dots on the plot are scattered roughly as a circle. This indicates that the relationship (covariation) between the two variables is:

"As the ownership of DVD players goes up, DVD rentals at Blockbuster will also go up." This statement illustrates the concept of:

In a regression analysis, the strength of the relationship between the independent and dependent variables is indicated by:

For a given sample, which of the following correlation coefficients is most likely to be found statistically significant?

Which of the following statements is false regarding the beta coefficient?

When the correlation coefficient is weak, it is possible that an association exists but it is not linear.

The statistical procedure that results in predictions with the lowest sum of squared differences between actual and predicted values in a regression equation is called:

Regression analysis assumes there is a straight line relationship between the independent and dependent variables.

r ² describes the amount of variation in the dependent variable that is associated with the variation in the independent variable.

The least squares procedure determines the best-fitting line by minimizing the vertical distances of all the data points from the line.

In multiple regression, the value of beta coefficient can never be greater than 1.

In the formula Y = a + bX + e_i, Y is the dependent variable.

Bivariate regression has only one independent variable.

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

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Exam 12: Examining Relationships in Quantitative Research

In bivariate regression analysis, the procedure used to determine the best fitting line is called the:

If the correlation coefficient is between 0.0 and 0.2, then there is a good chance the null hypothesis will be rejected.

Discuss the relationship between the Pearson correlation coefficient and the coefficient of determination.

A scatter plot wherein the dots form an ellipse can be described as a positive relationship.

In a regression analysis, the horizontal distance between the estimated regression line and the actual data points is the unexplained variance called error.

A researcher writes the general formula for a straight line. In this formula, the dependent variable is sales and the independent variable is advertising expenditure. In this formula, the amount of sales that will be realized when the advertising expenditure is zero, is represented by the symbol:

A researcher plots a scatter diagram of two variables. The dots on the plot are scattered roughly as a circle. This indicates that the relationship (covariation) between the two variables is:

"As the ownership of DVD players goes up, DVD rentals at Blockbuster will also go up." This statement illustrates the concept of:

In a regression analysis, the strength of the relationship between the independent and dependent variables is indicated by:

For a given sample, which of the following correlation coefficients is most likely to be found statistically significant?

Which of the following statements is false regarding the beta coefficient?

When the correlation coefficient is weak, it is possible that an association exists but it is not linear.

The statistical procedure that results in predictions with the lowest sum of squared differences between actual and predicted values in a regression equation is called:

Regression analysis assumes there is a straight line relationship between the independent and dependent variables.

r 2 describes the amount of variation in the dependent variable that is associated with the variation in the independent variable.

The least squares procedure determines the best-fitting line by minimizing the vertical distances of all the data points from the line.

In multiple regression, the value of beta coefficient can never be greater than 1.

In the formula Y = a + bX + ei, Y is the dependent variable.

Bivariate regression has only one independent variable.

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

r ² describes the amount of variation in the dependent variable that is associated with the variation in the independent variable.

In the formula Y = a + bX + e_i, Y is the dependent variable.