Question 1

When the descriptors on a scale measure levels or amounts (i.e. ,the level of sales dollars),the scale is categorical (nominal or ordinal).

Accepted Answer

A) True 
 B)False

Question 2

Both low-level and high-level scales can incorporate very precise linear relationships.

Accepted Answer

A) True 
 B)False

Question 3

Associative analyses determine whether stable relationships exist between:

Accepted Answer

A) costs and expenses. 
B) two variables. 
C) 12 or more variables. 
D) marketing and sales. 
E) statistics and results. 
A) costs and expenses. 
B) two variables. 
C) 12 or more variables. 
D) marketing and sales. 
E) statistics and results.

Question 4

When a consistent and systematic relationship is found between two variables,the linkage is:

Accepted Answer

A) causal. 
B) statistical. 
C) managerially significant. 
D) important. 
E) relevant. 
A) causal. 
B) statistical. 
C) managerially significant. 
D) important. 
E) relevant.

Question 5

With the information used to construct a cross-tabulation table,a column percentages table can also be constructed,but a row percentages table cannot.

Accepted Answer

A) True 
 B)False

Question 6

We would use the Pearson correlation table if we wanted to visualize the nonmonotonic relationship between two nominal scaled variables.

Accepted Answer

A) True 
 B)False

Question 7

The Pearson product moment correlation measures the linear relationship between two nominal and/or ordinal scaled variables.

Accepted Answer

A) True 
 B)False

Question 8

The key to establishing a monotonic relationship between two variables is determining if there is a general direction (increasing or decreasing)between the two variables.

Accepted Answer

A) True 
 B)False

Question 9

Presence refers to the strength of a relationship between three or more variables.

Accepted Answer

A) True 
 B)False

Question 10

A correlation coefficient is an index number constrained to fall between the range of:

Accepted Answer

A) 0 and 1.00. 
B) 0 and 100. 
C) -1.00 and +1.00. 
D) -1.00 and 0. 
E) -100 and 0. 
A) 0 and 1.00. 
B) 0 and 100. 
C) -1.00 and +1.00. 
D) -1.00 and 0. 
E) -100 and 0.

Question 11

Michelle Steward is a marketing professor at Wake Forest University.Michelle had been asked by the administration to study a sample of classes at Wake to help the university understand the student population better particularly in terms of factors that differentiate students with high versus low GPAs.One of the questions asked was,"What score did you earn (0 to 100)on the last test that you took?" and another question in the study asked,"How much time,estimated in numbers of minutes,did you study for the last test you took?" Michelle decided to run a cross-tabulation analysis on these two questions.When she did,she also ran the chi-square test.The result was a Pearson Chi-Square Value of 8.64 and a p value reported as a "Sig." in SPSS of .03.Michelle knew that this meant:

Accepted Answer

A) there was a significant,positive association between the two variables. 
B) there was the presence of an association;the probability of supporting the null hypothesis that there is no association is only 3 percent. 
C) there was the presence of a negative association;the probability of supporting the null hypothesis that there is no association is only 3 percent. 
D) there was the presence of a positive,"very strong" association because the probability of supporting the null hypothesis that there is no association is only .03 percent. 
E) None of the above;Michelle should not have run a chi-square test because the two variables are both metric. 
A) there was a significant,positive association between the two variables. 
B) there was the presence of an association;the probability of supporting the null hypothesis that there is no association is only 3 percent. 
C) there was the presence of a negative association;the probability of supporting the null hypothesis that there is no association is only 3 percent. 
D) there was the presence of a positive,"very strong" association because the probability of supporting the null hypothesis that there is no association is only .03 percent. 
E) None of the above;Michelle should not have run a chi-square test because the two variables are both metric.

Question 12

You do not have a "relationship" that links the labels (or levels)for two variables unless the relationship is:

Accepted Answer

A) causal and consistent. 
B) consistent and systematic. 
C) systematic and causal. 
D) systematic and important. 
E) consistent and important. 
A) causal and consistent. 
B) consistent and systematic. 
C) systematic and causal. 
D) systematic and important. 
E) consistent and important.

Question 13

Cross-tabulation tables allow us to look at two variables simultaneously and are arranged in a row and column format.

Accepted Answer

A) True 
 B)False

Question 14

If you wished to compute a Pearson product moment correlation coefficient using SPSS,which command sequence would you use?

Accepted Answer

A) CORRELATE;PEARSON;GO 
B) ANALYZE;CORRELATE;PEARSON 
C) ANALYZE;CORRELATE;PEARSON;R 
D) ANALYZE;CORRELATE;PEARSON;GO 
E) ANALYZE;CORRELATE;BIVARIATE 
A) CORRELATE;PEARSON;GO 
B) ANALYZE;CORRELATE;PEARSON 
C) ANALYZE;CORRELATE;PEARSON;R 
D) ANALYZE;CORRELATE;PEARSON;GO 
E) ANALYZE;CORRELATE;BIVARIATE

Question 15

If you were to find a significant association between two nominally scaled variables,a good way to present the findings in your cross-tabulation table would be to use:

Accepted Answer

A) a p value for each nonmonotonic relationship found. 
B) a Sig.value for each nonmonotonic relationship found. 
C) graphical presentations. 
D) numerical presentations that clearly indicate the direction and strength of the relationship. 
E) numerical presentations that clearly indicate the linear values in the relationship. 
A) a p value for each nonmonotonic relationship found. 
B) a Sig.value for each nonmonotonic relationship found. 
C) graphical presentations. 
D) numerical presentations that clearly indicate the direction and strength of the relationship. 
E) numerical presentations that clearly indicate the linear values in the relationship.

Question 16

Which of the following are caveats of correlation?

Accepted Answer

A) Its use is limited to metric variables (interval or ratio scaled). 
B) It examines the relationship between only two variables. 
C) Do not assume cause and effect. 
D) It is limited to linear relationships. 
E) all of the above 
A) Its use is limited to metric variables (interval or ratio scaled). 
B) It examines the relationship between only two variables. 
C) Do not assume cause and effect. 
D) It is limited to linear relationships. 
E) all of the above

Question 17

Which type of relationship is described by relationships that may be S-shaped or J-shaped?

Accepted Answer

A) causal relationship 
B) linear relationship 
C) curvilinear relationship 
D) nonmonotonic relationship 
E) irregular relationship 
A) causal relationship 
B) linear relationship 
C) curvilinear relationship 
D) nonmonotonic relationship 
E) irregular relationship

Question 18

The advertising director in your firm announced her resignation this morning to take another job,and she is leaving this afternoon.Your boss has asked you to take charge of advertising.Unfortunately,you learn the former director was just beginning planning for an upcoming promotion of one of the company's new products.Your immediate decision is to determine a brand name for the product.As the former director leaves,she stops by to drop off some marketing research reports she had just received,which includes several tests on brand names that were proposed for the new brand.The research company tested 30 potential brand names.For each brand name,they collected data on a number of variables such as "intention to purchase" and "attitude toward the brand name." All these variables were collected using 5-point intensity continuum scales.Thus,all the variables possess an interval level of measurement.Just focusing on the two variables mentioned ("intention to purchase" and "attitude toward the brand name"),what type of analysis would you conduct to help you make the decision?

Accepted Answer

A) Pearson product moment correlation analysis 
B) independent samples t tests 
C) cross-tabulation 
D) cross-tabulation with chi-square tests 
E) paired samples tabulation analysis 
A) Pearson product moment correlation analysis 
B) independent samples t tests 
C) cross-tabulation 
D) cross-tabulation with chi-square tests 
E) paired samples tabulation analysis

Question 19

Associative analyses determine whether stable relationships exist between two variables.

Accepted Answer

A) True 
 B)False

Question 20

Covariation is defined as the amount of change in one variable systematically associated with a change in another variable.

Accepted Answer

A) True 
 B)False

When the descriptors on a scale measure levels or amounts (i.e. ,the level of sales dollars),the scale is categorical (nominal or ordinal).

Both low-level and high-level scales can incorporate very precise linear relationships.

Associative analyses determine whether stable relationships exist between:

When a consistent and systematic relationship is found between two variables,the linkage is:

With the information used to construct a cross-tabulation table,a column percentages table can also be constructed,but a row percentages table cannot.

We would use the Pearson correlation table if we wanted to visualize the nonmonotonic relationship between two nominal scaled variables.

The Pearson product moment correlation measures the linear relationship between two nominal and/or ordinal scaled variables.

The key to establishing a monotonic relationship between two variables is determining if there is a general direction (increasing or decreasing)between the two variables.

Presence refers to the strength of a relationship between three or more variables.

A correlation coefficient is an index number constrained to fall between the range of:

You do not have a "relationship" that links the labels (or levels)for two variables unless the relationship is:

Cross-tabulation tables allow us to look at two variables simultaneously and are arranged in a row and column format.

If you wished to compute a Pearson product moment correlation coefficient using SPSS,which command sequence would you use?

If you were to find a significant association between two nominally scaled variables,a good way to present the findings in your cross-tabulation table would be to use:

Which of the following are caveats of correlation?

Which type of relationship is described by relationships that may be S-shaped or J-shaped?

Associative analyses determine whether stable relationships exist between two variables.

Covariation is defined as the amount of change in one variable systematically associated with a change in another variable.

Introduction to Marketing Research

The Marketing Research Industry

The Marketing Research Process Defining the Problem and Research Objectives

Research Design

Secondary Data Packaged Information

Utilizing Exploratory and Qualitative Research Techniques

Evaluating Survey Data Collection Methods

Understanding Measurement, developing Questions, and Designing the Questionnaire

Selecting the Sample

Determining the Size of a Sample

Dealing With Fieldwork and Data Quality

Using Basic Descriptive Analysis, performing Population Estimates, and Testing Hypotheses

Implementing Basic Differences Tests

Understanding Regression Analysis Basics

Writing the Research Report

Filters

Exam 14: Making Use of Associations Tests

When the descriptors on a scale measure levels or amounts (i.e. ,the level of sales dollars),the scale is categorical (nominal or ordinal).

Both low-level and high-level scales can incorporate very precise linear relationships.

Associative analyses determine whether stable relationships exist between:

When a consistent and systematic relationship is found between two variables,the linkage is:

With the information used to construct a cross-tabulation table,a column percentages table can also be constructed,but a row percentages table cannot.

We would use the Pearson correlation table if we wanted to visualize the nonmonotonic relationship between two nominal scaled variables.

The Pearson product moment correlation measures the linear relationship between two nominal and/or ordinal scaled variables.

The key to establishing a monotonic relationship between two variables is determining if there is a general direction (increasing or decreasing)between the two variables.

Presence refers to the strength of a relationship between three or more variables.

A correlation coefficient is an index number constrained to fall between the range of:

You do not have a "relationship" that links the labels (or levels)for two variables unless the relationship is:

Cross-tabulation tables allow us to look at two variables simultaneously and are arranged in a row and column format.

If you wished to compute a Pearson product moment correlation coefficient using SPSS,which command sequence would you use?

If you were to find a significant association between two nominally scaled variables,a good way to present the findings in your cross-tabulation table would be to use:

Which of the following are caveats of correlation?

Which type of relationship is described by relationships that may be S-shaped or J-shaped?

Associative analyses determine whether stable relationships exist between two variables.

Covariation is defined as the amount of change in one variable systematically associated with a change in another variable.

Introduction to Marketing Research

The Marketing Research Industry

The Marketing Research Process Defining the Problem and Research Objectives

Research Design

Secondary Data Packaged Information

Utilizing Exploratory and Qualitative Research Techniques

Evaluating Survey Data Collection Methods

Understanding Measurement, developing Questions, and Designing the Questionnaire

Selecting the Sample

Determining the Size of a Sample

Dealing With Fieldwork and Data Quality

Using Basic Descriptive Analysis, performing Population Estimates, and Testing Hypotheses

Implementing Basic Differences Tests

Understanding Regression Analysis Basics

Writing the Research Report

Filters