Question 1

________ derives a mathematical equation in the form of a straight line between a single metric criterion variable and a single metric predictor variable.

Accepted Answer

A)  Bivariate regression 
B)  Standard deviation 
C)  Standard error of the mean 
D)  Analysis of variance 
E)  Functional linear analysis 
A)  Bivariate regression 
B)  Standard deviation 
C)  Standard error of the mean 
D)  Analysis of variance 
E)  Functional linear analysis

Question 2

To standardize a variable,simply subtract the mean and divide the difference by the standard deviation.

Accepted Answer

A) True 
 B)False

Question 3

The term used to denote the standardized regression coefficient is called the ________.

Accepted Answer

A)  alpha coefficient 
B)  beta coefficient 
C)  gamma coefficient 
D)  theta coefficient 
E)  pi coefficient 
A)  alpha coefficient 
B)  beta coefficient 
C)  gamma coefficient 
D)  theta coefficient 
E)  pi coefficient

Question 4

The r² statistic measures the proportion of variation in one variable that is explained by the other.

Accepted Answer

A) True 
 B)False

Question 5

The difference between the observed value of Y and the value predicted by the regression equation is called the standard error.

Accepted Answer

A) True 
 B)False

Question 6

To estimate the accuracy of predicted values,it is useful to calculate the ________.

Accepted Answer

A)  analysis of variance 
B)  correlation coefficient 
C)  standard error of estimate 
D)  residual 
E)  precision coefficient 
A)  analysis of variance 
B)  correlation coefficient 
C)  standard error of estimate 
D)  residual 
E)  precision coefficient

Question 7

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

Accepted Answer

A) True 
 B)False

Question 8

A systematic relationship between two variables in which a change in one implies a corresponding change in the other is called covariance.

Accepted Answer

A) True 
 B)False

Question 9

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.

Accepted Answer

A)  correlation errors 
B)  standard error of the mean 
C)  sum of the squared errors 
D)  random distribution error 
E)  distance log 
A)  correlation errors 
B)  standard error of the mean 
C)  sum of the squared errors 
D)  random distribution error 
E)  distance log

Question 10

The correlation coefficient between two variables varies depending on their underlying units of measurement.

Accepted Answer

A) True 
 B)False

Question 11

The covariance may be either positive or negative.

Accepted Answer

A) True 
 B)False

Question 12

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

Accepted Answer

A) True 
 B)False

Question 13

An equation used to explain the results of multiple regression analysis is called the multiple regression model.

Accepted Answer

A) True 
 B)False

Question 14

Questionnaire development is a step involved in conducting bivariate regression analysis.

Accepted Answer

A) True 
 B)False

Question 15

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

Accepted Answer

A) True 
 B)False

Question 16

According to the text,the beta coefficient is also called the ________.

Accepted Answer

A)  beta factor 
B)  beta variable 
C)  beta element 
D)  beta weight 
E)  beta carotene 
A)  beta factor 
B)  beta variable 
C)  beta element 
D)  beta weight 
E)  beta carotene

Question 17

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

Accepted Answer

A)  Correlation analysis 
B)  Significance testing 
C)  Regression analysis 
D)  Factor analysis 
E)  Residual analysis 
A)  Correlation analysis 
B)  Significance testing 
C)  Regression analysis 
D)  Factor analysis 
E)  Residual analysis

Question 18

Which of the following is (are)true?

Accepted Answer

A)  r² = explained variation / total variation 
B)  r² = SSx / SSy 
C)  r² = (total variation - error variation) / total variation 
D)  r² = (SSy - SSerror) / SSy 
E)  All of the above are true. 
A)  r² = explained variation / total variation 
B)  r² = SSx / SSy 
C)  r² = (total variation - error variation) / total variation 
D)  r² = (SSy - SSerror) / SSy 
E)  All of the above are true.

Question 19

A scatter diagram is a plot of the values of two variables for all the cases or observations.

Accepted Answer

A) True 
 B)False

Question 20

________ is a statistical technique that simultaneously develops a mathematical relationship between two or more independent variables and an interval-scaled dependent variable.

Accepted Answer

A)  Product moment correlation 
B)  Standard regression 
C)  Factor analysis 
D)  Multiple regression 
E)  Canonical correlation 
A)  Product moment correlation 
B)  Standard regression 
C)  Factor analysis 
D)  Multiple regression 
E)  Canonical correlation

________ derives a mathematical equation in the form of a straight line between a single metric criterion variable and a single metric predictor variable.

To standardize a variable,simply subtract the mean and divide the difference by the standard deviation.

The term used to denote the standardized regression coefficient is called the ________.

The r² statistic measures the proportion of variation in one variable that is explained by the other.

The difference between the observed value of Y and the value predicted by the regression equation is called the standard error.

To estimate the accuracy of predicted values,it is useful to calculate the ________.

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

A systematic relationship between two variables in which a change in one implies a corresponding change in the other is called covariance.

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 correlation coefficient between two variables varies depending on their underlying units of measurement.

The covariance may be either positive or negative.

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

An equation used to explain the results of multiple regression analysis is called the multiple regression model.

Questionnaire development is a step involved in conducting bivariate regression analysis.

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

According to the text,the beta coefficient is also called the ________.

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

Which of the following is (are)true?

A scatter diagram is a plot of the values of two variables for all the cases or observations.

________ is a statistical technique that simultaneously develops a mathematical relationship between two or more independent variables and an interval-scaled dependent variable.

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

Exam 18: Correlation and Regression

________ derives a mathematical equation in the form of a straight line between a single metric criterion variable and a single metric predictor variable.

To standardize a variable,simply subtract the mean and divide the difference by the standard deviation.

The term used to denote the standardized regression coefficient is called the ________.

The r² statistic measures the proportion of variation in one variable that is explained by the other.

The difference between the observed value of Y and the value predicted by the regression equation is called the standard error.

To estimate the accuracy of predicted values,it is useful to calculate the ________.

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

A systematic relationship between two variables in which a change in one implies a corresponding change in the other is called covariance.

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 correlation coefficient between two variables varies depending on their underlying units of measurement.

The covariance may be either positive or negative.

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

An equation used to explain the results of multiple regression analysis is called the multiple regression model.

Questionnaire development is a step involved in conducting bivariate regression analysis.

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

According to the text,the beta coefficient is also called the ________.

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

Which of the following is (are)true?

A scatter diagram is a plot of the values of two variables for all the cases or observations.

________ is a statistical technique that simultaneously develops a mathematical relationship between two or more independent variables and an interval-scaled dependent variable.

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