Question 1

The point estimates b0 and b1 in a regression analysis, tend to increase the total sum of squares.

Accepted Answer

A) True 
 B)False  False

Question 2

In analysis of variance, the hypothesis that the means are equal will be rejected if 
a) the total mean square error is significantly greater than either the explained or unexplained mean square error 
b) the total mean square error is significantly greater than the unexplained 
c) the mean square error explained is significantly greater than the mean square unexplained 
d) the mean square error unexplained is significantly greater than the mean square explained

Accepted Answer

D

Question 3

A regression model can be used to explain, predict and control the dependent variable, on the basis of independent variables.

Accepted Answer

A) True 
 B)False  True

Question 4

A regression analysis has shown that there is a definite, positive relationship between sales dependent variable) and advertising and sales promotion all units in dollars).The estimated relationship is sales = 3) advertising + 1) sales promotion + 1,500.Based on the given information

Accepted Answer

A) all marketing resources should be allocated to advertising, if possible. 
B) all marketing resources should be allocated to sales promotion, if possible. 
C) the allocation between advertising and sales promotion should be split in the ratio 3 to 1 in all circumstances. 
D) none of the above. 
A) all marketing resources should be allocated to advertising, if possible. 
B) all marketing resources should be allocated to sales promotion, if possible. 
C) the allocation between advertising and sales promotion should be split in the ratio 3 to 1 in all circumstances. 
D) none of the above.

Question 5

The model: Y =   +  X2 + e hypothesizes a curvilinear relationship between X and Y.

Accepted Answer

A) True 
 B)False

Question 6

Consider the following model: Y =  +  X +

Accepted Answer

A) The model involves one dependent and one independent variable. 
B) The parameters of the model are Y and X. 
C) The parameters of the model are   and  . 
D) e represents the error in the model. 
E) Which of the following statements is not true? 
A) The model involves one dependent and one independent variable. 
B) The parameters of the model are Y and X. 
C) The parameters of the model are   and  . 
D) e represents the error in the model. 
E) Which of the following statements is not true?

Question 7

Partial correlation coefficient is the measure of association between two variables controlling for the effect of one or more additional variables.

Accepted Answer

A) True 
 B)False

Question 8

A regression model can accurately predict the level of a dependent variable in a changing market environment.

Accepted Answer

A) True 
 B)False

Question 9

The measures of association represented by r and r2 are 
a) symmetric 
b) dependent 
c) asymmetric 
d) independent

Accepted Answer

Question 10

Which of the following data analysis techniques can be termed analysis of dependence techniques?

Accepted Answer

A) Correlation analysis 
B) Regression analysis 
C) Multidimensional scaling 
D) Cluster analysis 
A) Correlation analysis 
B) Regression analysis 
C) Multidimensional scaling 
D) Cluster analysis

Question 11

The difference between the actual and the predicted values in a regression equation is called residuals.

Accepted Answer

A) True 
 B)False

Question 12

The knowledge of the regression coefficient and the t value can suggest the extent of association an independent variable has on the dependent variable.

Accepted Answer

A) True 
 B)False

Question 13

In regression analysis, the dependent variable is sometimes called the predictor variable.

Accepted Answer

A) True 
 B)False

Question 14

In interpreting parameter coefficients,   indicates that if the independent variable X is changed by one unit, the dependent variable Y will change by   units.In multiple regression, we add the constraint that the values of all other independent variables remain constant.

Accepted Answer

A) True 
 B)False

Question 15

In the simple linear regression model, Y =   +   X + e,

Accepted Answer

A) the errors are assumed to be as likely to occur above the line as below the line. 
B) the errors are assumed to be more likely to occur above the line than below it. 
C) the errors are assumed to be more likely to occur below the line than above it. 
D) it is assumed that the error is larger for larger values of X. 
A) the errors are assumed to be as likely to occur above the line as below the line. 
B) the errors are assumed to be more likely to occur above the line than below it. 
C) the errors are assumed to be more likely to occur below the line than above it. 
D) it is assumed that the error is larger for larger values of X.

Question 16

Correlation analysis involves measuring the strength of the relationship between two variables.

Accepted Answer

A) True 
 B)False

Question 17

r2 is the square of the correlation between X and Y and also the square of the correlation between Ŷ and Y.

Accepted Answer

A) True 
 B)False

Question 18

When testing the hypothesis that, in fact,   = 0, the researcher is actually testing the hypothesis that the independent variable has no linear) effect on the dependent variable.

Accepted Answer

A) True 
 B)False

Question 19

If the standard deviation of X is approximated by s, then the standard deviation of the mean based on a sample size of n) is s/ n.

Accepted Answer

A) True 
 B)False

Question 20

The coefficient of determination r2) measure the ability of the model to predict, and is the ratio of the explained variation to the total variation

Accepted Answer

A) True 
 B)False

Exam 19: Correlation Analysis and Regression Analysis

The point estimates b0 and b1 in a regression analysis, tend to increase the total sum of squares.

A regression model can be used to explain, predict and control the dependent variable, on the basis of independent variables.

A regression analysis has shown that there is a definite, positive relationship between sales dependent variable) and advertising and sales promotion all units in dollars).The estimated relationship is sales = 3) advertising + 1) sales promotion + 1,500.Based on the given information

The model: Y = + X2 + e hypothesizes a curvilinear relationship between X and Y.

Consider the following model: Y = + X +

Partial correlation coefficient is the measure of association between two variables controlling for the effect of one or more additional variables.

A regression model can accurately predict the level of a dependent variable in a changing market environment.

The measures of association represented by r and r2 are a) symmetric b) dependent c) asymmetric d) independent

Which of the following data analysis techniques can be termed analysis of dependence techniques?

The difference between the actual and the predicted values in a regression equation is called residuals.

The knowledge of the regression coefficient and the t value can suggest the extent of association an independent variable has on the dependent variable.

In regression analysis, the dependent variable is sometimes called the predictor variable.

In the simple linear regression model, Y = + X + e,

Correlation analysis involves measuring the strength of the relationship between two variables.

r2 is the square of the correlation between X and Y and also the square of the correlation between Ŷ and Y.

When testing the hypothesis that, in fact, = 0, the researcher is actually testing the hypothesis that the independent variable has no linear) effect on the dependent variable.

If the standard deviation of X is approximated by s, then the standard deviation of the mean based on a sample size of n) is s/n.

The coefficient of determination r2) measure the ability of the model to predict, and is the ratio of the explained variation to the total variation

A Decision Making Perspective on Marketing Intelligence

Marketing Research in Practice

The Marketing Research Process

Research Design and Implementation

Secondary Sources of Marketing Data

Standardized Sources of Marketing Data

Marketing Research on the Internet

Information Collection: Qualitative and Observational Methods

Information From Respondents: Issues in Data Collection

Information From Respondents: Survey Methods

Attitude Measurement

Designing the Questionnaire

Experimentation

Sampling Fundamentals

Sample Size and Statistical Theory

Fundamentals of Data Analysis

Hypothesis Testing: Basic Concepts and Tests of Association

Hypothesis Testing: Means and Proportions

Discriminant, Factor and Cluster Analysis

Multidimensional Scaling and Conjoint Analysis

Presenting the Results

Marketing-Mix Measures

Brand and Customer Metrics

New Age Strategies

Filters

The point estimates b₀ and b₁ in a regression analysis, tend to increase the total sum of squares.

The model: Y = + X² + e hypothesizes a curvilinear relationship between X and Y.

The measures of association represented by r and r² are a) symmetric b) dependent c) asymmetric d) independent

r² is the square of the correlation between X and Y and also the square of the correlation between Ŷ and Y.

The coefficient of determination r²) measure the ability of the model to predict, and is the ratio of the explained variation to the total variation