Question 1

The four basic types of relationships between two variables are:

Accepted Answer

A)  anonmonotonic, duotonic, linear, and curvilinear 
B)  nonmonotonic, duotonic, sublinear, and curvilinear 
C)  nonmonotonic, monotonic, linear, and curvilinear 
D)  causal, consistent, systematic, and linear 
E)  duotonic, linear, sublinear, and alinear 
A)  anonmonotonic, duotonic, linear, and curvilinear 
B)  nonmonotonic, duotonic, sublinear, and curvilinear 
C)  nonmonotonic, monotonic, linear, and curvilinear 
D)  causal, consistent, systematic, and linear 
E)  duotonic, linear, sublinear, and alinear

Question 2

When we present findings on cross-tabulations with chi-square analysis, we cannot use the characteristics of direction or strength because we are dealing with categorical, or nominal scaled, variables.

Accepted Answer

A) True 
 B)False

Question 3

The owner of a shoe store knows that as children increase in age, their shoe size tends to get larger. This is an example of what type of relationship?

Accepted Answer

A)  causal relationship 
B)  duotonic relationship 
C)  monotonic relationship 
D)  nonmonotonic relationship 
E)  linear relationship 
A)  causal relationship 
B)  duotonic relationship 
C)  monotonic relationship 
D)  nonmonotonic relationship 
E)  linear relationship

Question 4

Pontiac wants to know what types of persons respond favorably to proposed style changes in the Firebird. Frito-Lay wants to know what kinds of people buy from the Frito-Lay line. These are questions that may be answered through:

Accepted Answer

A)  relationship analysis 
B)  chi-square analysis 
C)  associative analysis 
D)  analysis of variance 
E)  regression analysis 
A)  relationship analysis 
B)  chi-square analysis 
C)  associative analysis 
D)  analysis of variance 
E)  regression analysis

Question 5

In the textbook you were given an example of running a chi-square test using SPSS. The output shows a "Pearson Chi-Square" value of 23.272. This value alone means:

Accepted Answer

A)  there is a significant difference 
B)  there is no significant difference 
C)  the difference is associative 
D)  the difference must immediately be rounded up 
E)  none of the above 
A)  there is a significant difference 
B)  there is no significant difference 
C)  the difference is associative 
D)  the difference must immediately be rounded up 
E)  none of the above

Question 6

The characteristic of direction, in describing the relationship between two variables, is applicable only when the relationship is either monotonic or linear.

Accepted Answer

A) True 
 B)False

Question 7

In chi-square, the null hypothesis states that there is no association. When the "Asymp. Sig." on the SPSS output is low, this means there is low support for the null hypothesis.

Accepted Answer

A) True 
 B)False

Question 8

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

Accepted Answer

A) True 
 B)False

Question 9

The logic of the chi-square test would argue that, for a significant relationship to exist:

Accepted Answer

A)  there should be large differences between the observed and expected frequencies 
B)  there should be few differences between the observed and expected frequencies 
C)  there should be no differences between the observed and expected frequencies 
D)  there should be negative differences between the observed and expected frequencies 
E)  there should be only one difference between the observed and expected frequencies 
A)  there should be large differences between the observed and expected frequencies 
B)  there should be few differences between the observed and expected frequencies 
C)  there should be no differences between the observed and expected frequencies 
D)  there should be negative differences between the observed and expected frequencies 
E)  there should be only one difference between the observed and expected frequencies

Question 10

When it comes to determining the statistical significance of the correlation coefficient, there are rules of thumb. For example, .81 to 1.00 is considered to be "strong."

Accepted Answer

A) True 
 B)False

Question 11

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 12

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

Accepted Answer

A) True 
 B)False

Question 13

When the descriptors on a scale measure levels or amounts, that is, the level of sales dollars, the scale is metric (interval or ratio).

Accepted Answer

A) True 
 B)False

Question 14

The Pearson Product Moment correlation measures the linear relationship between two:

Accepted Answer

A)  nominal- or ordinal-scaled variables 
B)  nominal- or interval-scaled variables 
C)  interval- or ratio-scaled variables 
D)  nominal- or ratio-scaled variables 
E)  ordinal- or interval-scaled variables 
A)  nominal- or ordinal-scaled variables 
B)  nominal- or interval-scaled variables 
C)  interval- or ratio-scaled variables 
D)  nominal- or ratio-scaled variables 
E)  ordinal- or interval-scaled variables

The four basic types of relationships between two variables are:

When we present findings on cross-tabulations with chi-square analysis, we cannot use the characteristics of direction or strength because we are dealing with categorical, or nominal scaled, variables.

The owner of a shoe store knows that as children increase in age, their shoe size tends to get larger. This is an example of what type of relationship?

Pontiac wants to know what types of persons respond favorably to proposed style changes in the Firebird. Frito-Lay wants to know what kinds of people buy from the Frito-Lay line. These are questions that may be answered through:

In the textbook you were given an example of running a chi-square test using SPSS. The output shows a "Pearson Chi-Square" value of 23.272. This value alone means:

The characteristic of direction, in describing the relationship between two variables, is applicable only when the relationship is either monotonic or linear.

In chi-square, the null hypothesis states that there is no association. When the "Asymp. Sig." on the SPSS output is low, this means there is low support for the null hypothesis.

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

The logic of the chi-square test would argue that, for a significant relationship to exist:

When it comes to determining the statistical significance of the correlation coefficient, there are rules of thumb. For example, .81 to 1.00 is considered to be "strong."

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

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

When the descriptors on a scale measure levels or amounts, that is, the level of sales dollars, the scale is metric (interval or ratio).

The Pearson Product Moment correlation measures the linear relationship between two:

Introduction to Marketing Research

The Marketing Research Process

The Marketing Research Industry

Defining the Problem and Determining Research Objectives

Research Design

Using Secondary Data and Online Information Databases

Standardized Information Sources

Observation, Focus Groups, and Other Qualitative Methods

Survey Data-Collection Methods

Measurement in Marketing Research

Designing the Questionnaire

Determining How to Select the Sample

Determining the Size of a Sample

Data Collection in the Field, Nonresponse Error, and Questionnaire Screening

Basic Data Analysis: Descriptive Statistics

Generalizing a Sample's Findings to its Population and Testing Hypotheses About Percents and Means

Testing for Differences Between Two Groups or Among More Than

Regression Analysis in Marketing Research

The Marketing Research Report: Preparation and Presentation

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Exam 18: Determining and Interpreting Associations Among Variables

The four basic types of relationships between two variables are:

When we present findings on cross-tabulations with chi-square analysis, we cannot use the characteristics of direction or strength because we are dealing with categorical, or nominal scaled, variables.

The owner of a shoe store knows that as children increase in age, their shoe size tends to get larger. This is an example of what type of relationship?

Pontiac wants to know what types of persons respond favorably to proposed style changes in the Firebird. Frito-Lay wants to know what kinds of people buy from the Frito-Lay line. These are questions that may be answered through:

In the textbook you were given an example of running a chi-square test using SPSS. The output shows a "Pearson Chi-Square" value of 23.272. This value alone means:

The characteristic of direction, in describing the relationship between two variables, is applicable only when the relationship is either monotonic or linear.

In chi-square, the null hypothesis states that there is no association. When the "Asymp. Sig." on the SPSS output is low, this means there is low support for the null hypothesis.

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

The logic of the chi-square test would argue that, for a significant relationship to exist:

When it comes to determining the statistical significance of the correlation coefficient, there are rules of thumb. For example, .81 to 1.00 is considered to be "strong."

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

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

When the descriptors on a scale measure levels or amounts, that is, the level of sales dollars, the scale is metric (interval or ratio).

The Pearson Product Moment correlation measures the linear relationship between two:

Introduction to Marketing Research

The Marketing Research Process

The Marketing Research Industry

Defining the Problem and Determining Research Objectives

Research Design

Using Secondary Data and Online Information Databases

Standardized Information Sources

Observation, Focus Groups, and Other Qualitative Methods

Survey Data-Collection Methods

Measurement in Marketing Research

Designing the Questionnaire

Determining How to Select the Sample

Determining the Size of a Sample

Data Collection in the Field, Nonresponse Error, and Questionnaire Screening

Basic Data Analysis: Descriptive Statistics

Generalizing a Sample's Findings to its Population and Testing Hypotheses About Percents and Means

Testing for Differences Between Two Groups or Among More Than

Regression Analysis in Marketing Research

The Marketing Research Report: Preparation and Presentation

Filters