Deck 17: Bivariate Correlation and Regression

Question 1

What are the possible values in correlation analysis?

A)0 to 1
B)-1 to +1
C)-1 to 0
D)-.99 to + .99
E)-2 to +2

Answer 1

B

Question 2

Which test statistic is used to test the significance of the results of a regression analysis?

A)F
B)t
C)Z
D)chi-square
E)least square

Answer 2

A

Question 3

In regression,the higher the _________ value,the more likely the relationship between variables is significant.

A)F
B)p
C)Z
D)t
E)none of these

Answer 3

A

Question 4

____________ is the mathematical technique for fitting a line that best describes the relationship between two variables.

A)Pearson's product-moment correlation
B)Least squares procedure
C)Chi-square test
D)Significance test
E)none of these

Question 5

If a marketer wants to correlate an ordinal ranking of TV sets with the nominal scale variable gender,the marketer would have to use_____________.

A)ANOVA
B)Pearson's product-moment correlation
C)z-test
D)chi-square test
E)none of these

Question 6

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

Question 7

An R² of .05 would indicate:

A)a significant relationship between X and Y.
B)a negative relationship between X and Y.
C)a very weak relationship between X and Y.
D)none of these

Question 8

When the value of one variable increases at exactly the same rate as another variable decreases,this is said to be a ___________________relationship.

A)strong positive linear
B)positive linear
C)perfect negative linear
D)parabolic
E)strong curvilinear association

Question 9

Research on fear appeal in advertising suggests that a moderate amount of fear is most effective at achieving persuasion.That is,using not enough fear or too much fear in advertising will not be effective.This is an example of what type of relationship that regression might find?

A)positive linear
B)negative linear
C)curvilinear
D)no relationship
E)none of these

Question 10

When two variables are not correlated at all,the correlation coefficient would be _______.

A)-1
B)0
C)1
D)-2
E)0.5

Question 11

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

Question 12

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

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

Question 13

In a regression output in SPSS,R² represents:

A)the independent variable.
B)the dependent variable.
C)the estimated slope of the regression line.
D)the coefficient of determination.

Question 14

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

Question 15

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

Question 16

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.

Question 17

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

Question 18

A correlation analysis between sales and sales training scores results in R = +.98.Which of the following best interprets the relationship between sales and sales training?

A)98% of the salespeople taking the test have higher sales.
B)The correlation between sales and sales training is very weak and insignificant.
C)The correlation between sales and sales training is strong and positive, indicating that higher sales training scores are closely associated with higher sales and vice-versa.
D)98% of the variation in sales is explained by variations in sales training scores.
E)none of these

Question 19

A regression equation that estimates the number of hours of study that impact a test score would most likely produce what type of relationship?

A)positive
B)negative
C)curvilinear
D)none of these

Question 20

Bivariate regression can not demonstrate:

A)when the two variables are linear.
B)when the two variables are strongly inversely related.
C)when the two variables are strongly positively related.
D)when the two variables are causally related.

Question 21

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

Question 22

_______________ 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

Question 23

Dependent variables are also known as predictor variables.

Question 24

In a regression equation,which symbol represents the dependent variable?

A)Y
B)X
C)e
D)r
E)p

Question 25

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

Question 26

The coefficient of determination is used in correlation analysis.

Question 27

The dependent variable is also called the __________________.

A)Measure
B)Criterion
C)Principle
D)Standard
E)Predictor

Question 28

A R = -.95 is always weaker than +.95,because positive relationships are more significant than negative relationships.

Question 29

A perfect correlation indicates that two variables are causally related.

Question 30

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

Question 31

In correlation analysis,the closer the value of R is to -1 or +1,the stronger the correlation between the two variables in question.

Question 32

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

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

Question 33

The degree to which changes in one variable (the dependent variable)are associated with changes in another is which of the following?

A)correlation
B)consideration
C)regression
D)association
E)none of these

Question 34

A scatter plot compares actual data to a predicted relationship between 2 variables.

Question 35

An R² of 0 indicates no relationship between variables.

Question 36

The variation explained by the regression equation is called SSR or sum of squares due to the regression.

Question 37

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

Question 38

The R² statistic ranges from -1 to 1.

Question 39

Which of the following is not included in the equation for the coefficient of determination?

A)explained variation
B)total variation
C)estimated variation
D)unexplained variation

Question 40

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

Question 41

Explain the meaning of the coefficient of determination.What does this coefficient tell the researcher about the nature of the relationship between the dependent and independent variables?

Question 42

In regression,the unexplained variation is referred to as error sum of squares (SSE).

Question 43

In the equation for regression analysis,the letter X represents the independent variable.

Question 44

The correct formula for the analysis of variance used to test the significance of results is F = MSR / MSE.

Question 45

Which of the relationships in the matrix is the strongest?

Question 46

How would you interpret the relationship between Education and Age?

Question 47

How many pairs of responses were in this correlation analysis? ________

Question 48

Some of the results of a regression analysis are as follows:
SSE = 52,500 SST = 485,200
Compute the Coefficient of Determination (R²)and interpret.

Question 49

Draw a graph depicting a strong but inverse correlation between X(Sales)and
number of times the sales force did not reach its quota.Interpret the relationship.

Question 50

The coefficient of correlation describes the degree of association between X and Y.

Question 51

Interpret the correlation coefficient for the following data: