Deck 17: A: Bivariate Correlation and Regression

Question 1

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 the above

Answer 1

A

Question 2

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

A)independent
B)coefficient
C)dependent
D)none of the above

Answer 2

C

Question 3

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)none of the above

Answer 3

D

Question 4

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)none of the above

Question 5

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 6

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)none of the above

Question 7

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

A)F
B)p
C)Z
D)none of the above

Question 8

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

A)-1
B)0
C)1
D)-2
E)none of the above

Question 9

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 the above

Question 10

An R²of .05 would indicate:

A)a significant relationship between X and Y.
B)a negative relationship between X and Y.
C)a very small relationship between X and Y.
D)none of the above

Question 11

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)none of the above

Question 12

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 the above

Question 13

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 the above

Question 14

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)none of the above

Question 15

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 the above

Question 16

____________ 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 the above

Question 17

Which of the following techniques requires at 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 18

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

A)Y
B)X
C)e
D)r
E)none of the above

Question 19

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 the above

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

The R² statistic ranges from -1 to 1.

Question 22

Bivariate regression looks at the relationship between many variables.

Question 23

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

Question 24

A perfect correlation indicates that two variables are causally related.

Question 25

The variation explained by the regression equation is called SSR or sum of squares due to the regression,and the variation not explained by the regression is called SSE or the error sum of squares.

Question 26

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

Question 27

_______________ 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)None of the above

Question 28

The coefficient of determination is used in correlation analysis.

Question 29

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

Question 30

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

Question 31

The dependent variable is also called the __________________.

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

Question 32

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 33

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

Question 34

Ordinal data cannot be analyzed using regression analysis.

Question 35

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 36

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

A)Bivariate techniques
B)Univariate techniques
C)Multivariate techniques
D)None of the above

Question 37

Dependent variables are also known as predictor variables.

Question 38

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

Question 39

An R²of 0 indicates no relationship between variables.

Question 40

What is the variation not explained by the regression?

A)Dependent variation
B)Error sum of squares
C)Neither A nor B
D)Both A and B

Question 41

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

Question 42

How would you interpret the relationship between Education and Age?

Question 43

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 44

Which of the relationships in the matrix is the strongest?

Question 45

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 46

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

Question 47

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

Question 48

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

Question 49

Interpret the correlation coefficient for the following data:
Sales Sales Training Score
45,000 98
34,500 74
23,750 57
51,450 99
41,000 85
The resulting correlation coefficient is +.98 and the probability of insignificance is 3%.