Exam 18: Correlation and Regression

A technique for fitting a straight line to a scattergram by minimizing the sum of the squares of the vertical distances of all the points from the line is called the ________.

(Multiple Choice)

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Question 61

In multiple regression, the strength of association is measured by the square of the multiple correlation coefficient, which is called the ________.

(Multiple Choice)

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Question 62

When data are standardized, the intercept assumes a value of ________.

(Multiple Choice)

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Question 63

________ is a statistical procedure for analyzing associative relationships between a metric dependent variable and one or more independent variables.

(Multiple Choice)

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Question 64

Regression analysis is a statistical procedure for analyzing associative relationships between a metric dependent variable and one or more independent variables.

(True/False)

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Question 65

According to the text, the ________ measures the linear association between two metric variables.

(Multiple Choice)

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Question 66

A procedure for deriving a mathematical relationship, in the form of an equation, between a single metric dependent variable and a single metric independent variable is called univariate regression.

(True/False)

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Question 67

Both r and r² are symmetric measures of association. In other words, the correlation of X and Y is the same as the correlation of Y and X.

(True/False)

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Question 68

Standardization may be desirable because it is easier to compare the beta coefficients than it is to compare the raw coefficients.

(True/False)

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Question 69

A(n) ________ is a plot of the values of two variables for all the cases or observations.

(Multiple Choice)

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Question 70

The most commonly used technique for fitting a straight line to a scattergram is the least-squares procedure.

(True/False)

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Question 71

R² cannot decrease as more independent variables are added to the regression equation.

(True/False)

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Question 72

A procedure for deriving a mathematical relationship, in the form of an equation, between a single metric dependent variable and a single metric independent variable is called ________.

(Multiple Choice)

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Question 73

The distances for all the points on the regression line are squared and added together to compute the ________, which is a measure of total error.

(Multiple Choice)

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Question 74

The ________ is the most widely used statistic that summarizes the strength and direction of association between two metric variables.

(Multiple Choice)

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Question 75

All of the following are true EXCEPT:

(Multiple Choice)

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Question 76

________ involves testing the significance of the overall regression equation as well as specific partial regression coefficients.

(Multiple Choice)

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Question 77

The strength of association is measured by the ________.

(Multiple Choice)

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Question 78

When r = 0, this means that X and Y are unrelated.

(True/False)

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Question 79

When determining the correlation coefficient, r, it does matter which variable is considered to be the dependent variable and which the independent.

(True/False)

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Question 80

Showing 61 - 80 of 90

A technique for fitting a straight line to a scattergram by minimizing the sum of the squares of the vertical distances of all the points from the line is called the ________.

In multiple regression, the strength of association is measured by the square of the multiple correlation coefficient, which is called the ________.

When data are standardized, the intercept assumes a value of ________.

________ is a statistical procedure for analyzing associative relationships between a metric dependent variable and one or more independent variables.

Regression analysis is a statistical procedure for analyzing associative relationships between a metric dependent variable and one or more independent variables.

According to the text, the ________ measures the linear association between two metric variables.

A procedure for deriving a mathematical relationship, in the form of an equation, between a single metric dependent variable and a single metric independent variable is called univariate regression.

Both r and r² are symmetric measures of association. In other words, the correlation of X and Y is the same as the correlation of Y and X.

Standardization may be desirable because it is easier to compare the beta coefficients than it is to compare the raw coefficients.

A(n) ________ is a plot of the values of two variables for all the cases or observations.

The most commonly used technique for fitting a straight line to a scattergram is the least-squares procedure.

R² cannot decrease as more independent variables are added to the regression equation.

A procedure for deriving a mathematical relationship, in the form of an equation, between a single metric dependent variable and a single metric independent variable is called ________.

The distances for all the points on the regression line are squared and added together to compute the ________, which is a measure of total error.

The ________ is the most widely used statistic that summarizes the strength and direction of association between two metric variables.

All of the following are true EXCEPT:

________ involves testing the significance of the overall regression equation as well as specific partial regression coefficients.

The strength of association is measured by the ________.

When r = 0, this means that X and Y are unrelated.

When determining the correlation coefficient, r, it does matter which variable is considered to be the dependent variable and which the independent.

Introduction to Marketing Research

Defining the Marketing Research Problem and Developing an Approach

Research Design

Exploratory Research Design: Secondary Data

Exploratory Research Design: Syndicated Sources of Secondary Data

Exploratory Research Design: Qualitative Research

Descriptive Research Design: Survey and Observation

Causal Research Design: Experimentation

Measurement and Scaling: Fundamentals and Comparative Scaling

Measurement and Scaling: Noncomparative Scaling Techniques

Questionnaire and Form Design

Sampling: Design and Procedures

Sampling: Final and Initial Sample Size Determination

Fieldwork: Data Collection

Data Preparation and Analysis Strategy

Frequency Distribution, Hypothesis Testing, and Cross-Tabulation

Hypothesis Testing Related to Differences

Report Preparation and Presentation

Filters