MKT301 - Chap 12

c

"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.

d

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

e

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.

d

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

b

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

d

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.

a

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.

e

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

c

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

d

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

c

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

b

In a bivariate regression analysis, there is/are _____ predictor variable(s). a. 0 b. 1 c. 2 d. 3 e. 4

b

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.

d

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.

a

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.

e

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.

b

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?

c

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. 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. d. used in situations where several independent variables are highly correlated with each other. e. never statistically significant.

c

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.

b

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

b

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?

a

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

a

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.

d

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 ranges from .00 to 1.00, and can be either positive or negative. d. A negative beta means as the size of the independent variable decreases then the size of the dependent variable gets smaller. e. It removes the effects of using different scales of measurement.

a

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. direction c. presence d. type e. dispersion