Deck 12: Examining Relationships in Quantitative Research

Question 1

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?

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

Answer 1

C

Question 2

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:

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

Answer 2

C

Question 3

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

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

Answer 3

C

Question 4

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:

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

Question 5

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

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 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:

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

Question 7

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:

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

Question 8

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.

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

Question 9

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

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

Question 10

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:

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 11

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.

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

Question 12

The coefficient of determination:

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 13

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

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

Question 14

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.

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

Question 15

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

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 16

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

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 17

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

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

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?

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

Question 19

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

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 20

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

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

Question 21

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

Question 22

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

Question 23

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

Question 24

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

Question 25

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

Question 26

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.

Question 27

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

Question 28

The model F-statistic is:

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 29

Bivariate regression has only one independent variable.

Question 30

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

Question 31

Multicollinearity is:

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 32

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

Question 33

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

Question 34

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

Question 35

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

Question 36

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

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 37

Independent variables are also called predictor variables.

Question 38

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

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

Question 39

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

Question 40

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

A)the regression coefficient.
B)the r².
C)the significance level.
D)the t statistic.
E)the beta coefficient.

Question 41

Discuss the problem of multicollinearity encountered in multiple regression analysis.

Question 42

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

Question 43

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.

Question 44

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

Question 45

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

Question 46

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

Question 47

Explain the concept of covariation.

Question 48

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

Question 49

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

Question 50

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