Exam 19: Correlation Analysis and Regression Analysis

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Although the least-squares regression line provides a reasonable fit of the data points, there are some deviations in the sample data about the line.

(True/False)

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Question 21

A 95% confidence interval means

(Multiple Choice)

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Question 22

The Pearson correlation coefficient measures the degree to which there is a linear association between two intervally scaled variables.

(True/False)

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Question 23

The unexplained variation in Y is estimated by n ^ $\Sigma$ Y_i - Y₁)² i=1

(True/False)

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Question 24

An independent variable which takes a small number 3 or 4) of discrete values is often termed a dummy variable.

(True/False)

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Question 25

There are ______ degrees of freedom associated with a sample variance

(Multiple Choice)

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Question 26

In analysis of variance, if RHO = 0, the explained variance is

(Multiple Choice)

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Question 27

Regression is an analysis of dependence technique since it involves a dependent variable as the focus of analysis.

(True/False)

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Question 28

One of the best ways to analyze relationships between two sets of nominal data is by doing

(Multiple Choice)

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Question 29

To examine the association between two variables after controlling for the other variables the researcher should use

(Multiple Choice)

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Question 30

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

(True/False)

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Question 31

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

(True/False)

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Question 32

^ Consider the estimated relationship: Y = 50 + 50X. 1-The average level of Y, if X = 0, is 50. 2-For each unit increase in $\alpha$ , Y will increase by 50 units. 3-For each unit increase in X, Y will increase by 50 units.

(Multiple Choice)

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Question 33

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

(True/False)

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Question 34

A least squares criterion minimizes the squared vertical deviations from the regression line.

(True/False)

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Question 35

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

(True/False)

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Question 36

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

(True/False)

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Question 37

A confidence coefficient is denoted by the symbol

(Multiple Choice)

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Question 38

Consider the following: Based on the above information, which of these statements is not true? ^

(Multiple Choice)

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Question 39

A term used to characterize the relative flatness or peakedness of a distribution of variable values is

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Question 40

Showing 21 - 40 of 52

Exam 19: Correlation Analysis and Regression Analysis

Although the least-squares regression line provides a reasonable fit of the data points, there are some deviations in the sample data about the line.

A 95% confidence interval means

The Pearson correlation coefficient measures the degree to which there is a linear association between two intervally scaled variables.

The unexplained variation in Y is estimated by n ^ Σ\SigmaΣ Yi - Y1)2 i=1

An independent variable which takes a small number 3 or 4) of discrete values is often termed a dummy variable.

There are ______ degrees of freedom associated with a sample variance

In analysis of variance, if RHO = 0, the explained variance is

Regression is an analysis of dependence technique since it involves a dependent variable as the focus of analysis.

One of the best ways to analyze relationships between two sets of nominal data is by doing

To examine the association between two variables after controlling for the other variables the researcher should use

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

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

^ Consider the estimated relationship: Y = 50 + 50X. 1-The average level of Y, if X = 0, is 50. 2-For each unit increase in α\alphaα , Y will increase by 50 units. 3-For each unit increase in X, Y will increase by 50 units.

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

A least squares criterion minimizes the squared vertical deviations from the regression line.

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

The model: Y = α\alphaα + β\betaβ X2 + e hypothesizes a curvilinear relationship between X and Y.

A confidence coefficient is denoted by the symbol

Consider the following: Based on the above information, which of these statements is not true? ^

A term used to characterize the relative flatness or peakedness of a distribution of variable values is

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

Ttitude Measurement

Signing the Questionnaire

Xperimentation

Sampling Fundamentals

Sample Size and Statistical Theory

Fundamentals of Data Analysis

Hypothesis Testing: Basic Concepts and Tests of Association

Hypothesis Testing: Means and Proportions

Iscriminant, Factor and Cluster Analysis

Multidimensional Scaling and Conjoint Analysis

Presenting the Results

Marketing-Mix Measures

Ontemporary Applications of Marketing Intelligence

Atabase Marketing, E-Commerce, Relationship

Filters

The unexplained variation in Y is estimated by n ^ $\Sigma$ Y_i - Y₁)² i=1

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

^ Consider the estimated relationship: Y = 50 + 50X. 1-The average level of Y, if X = 0, is 50. 2-For each unit increase in $\alpha$ , Y will increase by 50 units. 3-For each unit increase in X, Y will increase by 50 units.

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

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