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_______________ refers to analysis is one of strength of the linear relationship between two variables when one is considered the independent variable and the other the dependent variable


A) Multivariate regression
B) Univariate regression
C) Bivariate regression
D) Trivariate regression
E) None of these

F) A) and E)
G) A) and B)

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A perfect correlation indicates that two variables are causally related.

A) True
B) False

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Given the Correlation Matrix below, to answer the following questions Given the Correlation Matrix below,  to answer the following questions   	Assume that respondents answered the questions with ratio scale responses.    -How many pairs of responses were in this correlation analysis? ________ Assume that respondents answered the questions with ratio scale responses. -How many pairs of responses were in this correlation analysis? ________

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The results in the matrix indi...

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Given the Correlation Matrix below, to answer the following questions : Given the Correlation Matrix below, to answer the following questions :   	Assume that respondents answered the questions with ratio scale responses.    -Which of the relationships in the matrix is the strongest? Assume that respondents answered the questions with ratio scale responses. -Which of the relationships in the matrix is the strongest?

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The strongest relationship is between AG...

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Which of the following is the appropriate technique for correlation analysis,which involves metric (interval or ratio) data?


A) Spearman's rank-order correlation
B) Jensen's analysis of covariance
C) Kendall's coefficient of concordance
D) Pearson's product-moment correlation
E) Edward's metric analysis

F) C) and D)
G) A) and B)

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One way to study the relationship between the dependent and independent variable is to plot the data in a scatter diagram.

A) True
B) False

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The R² statistic ranges from -1 to 1.

A) True
B) False

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Interpret the correlation coefficient for the following data: Interpret the correlation coefficient for the following data:

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There is a strong positive cor...

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The percentage of total variation in the dependent variable that is described by the independent variable is expressed by_________.


A) coefficient of determination
B) correlation coefficient
C) coefficient of covariation
D) regression coefficient
E) none of these

F) A) and D)
G) A) and E)

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If you are studying the impact of training on salesperson performance as indicated on an exam taken by salespersons at the end of training,salesperson sales would be the ____________ variable,and the salesperson exam score would be the _____________ variable.


A) criterion, predictor
B) covariate, independent
C) independent, predictor
D) dependent, independent
E) covariate, dependent

F) A) and E)
G) All of the above

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___________ are statistical methods of analyzing the relationship between two variables.


A) Bivariate techniques
B) Univariate techniques
C) Multivariate techniques
D) None of these

E) A) and C)
F) B) and D)

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Which of the following techniques requires that both variables are ratio or interval data?


A) bivariate regression
B) ANOVA
C) t test
D) Pearson's product-moment correlation
E) All are appropriate.

F) A) and E)
G) B) and D)

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In a regression equation,sales would typically be the ______________ variable.


A) independent
B) coefficient
C) dependent
D) none of these

E) B) and D)
F) A) and B)

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What is the variation not explained by the regression?


A) Sum of squares due to regression
B) Error sum of squares
C) Neither sum of squares due to regression or Error sum of squares
D) Both Sum of squares due to regression and Error sum of squares

E) A) and B)
F) B) and C)

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Bivariate statistical techniques are often used to establish cause and effect relationships between two or more variables.

A) True
B) False

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In bivariate regression,both the independent and dependent variables are measured in the form of nominal and/or ordinal data.

A) True
B) False

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  A) perfect linear association B) strong exponential association C) strong parabolic association D) no association E) strong curvilinear association


A) perfect linear association
B) strong exponential association
C) strong parabolic association
D) no association
E) strong curvilinear association

F) A) and B)
G) A) and E)

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The least squares estimation procedure often results in a perfectly straight line.

A) True
B) False

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The coefficient of determination is used in correlation analysis.

A) True
B) False

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The explained variation by the regression is referred to as the:


A) total variation.
B) bivariate.
C) sum of squares due to regression .
D) none of these

E) B) and D)
F) C) and D)

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