Deck 14: Examining Relationships Using Correlation and Regression

Question 1

Which of the following is a basic concept we need to understand about relationships between variables?

A) relationship presence
B) the nature of relationships
C) direction of relationships
D) strength of association
E) all of these choices

Answer 1

E

Question 2

_____ assesses whether a systematic relationship exists between two or more variables.

A) Strength of association
B) Presence
C) Nature of relationships
D) Direction
E) Statistical significance

Answer 2

B

Question 3

A _____ relationship is a straight-line association between two or more variables.

A) correlation
B) statistically significant
C) covariation
D) linear
E) nonlinear

Answer 3

D

Question 4

A _____ relationship, often referred to as curvilinear, is one in which the relationship is best described by a curve instead of a straight line.

A) correlation
B) statistically significant
C) covariation
D) linear
E) nonlinear

Question 5

_____ is when one variable consistently and systematically changes relative to another variable.

A) Correlation
B) Statistical significance
C) Covariation
D) Linearity
E) Nonlinearity

Question 6

The ______ measures the degree of covariation between two variables.

A) correlation coefficient
B) covariance coefficient
C) alpha
D) multicollinearity
E) statistical significance

Question 7

The size of the correlation coefficient is used to quantitatively describe the _____.

A) presence of a relationship
B) strength of the association
C) direction of the relationship
D) linearity of the relationship
E) multicollinearity of the relationship

Question 8

A _____ is an easy way to visually display the covariation between two variables and is a plot of the values of two variables for all the observations in the sample.

A) residual plot
B) normal distribution
C) scatter diagram
D) histogram
E) frequency distribution

Question 9

Sam wants to visually display the covariation between two variables. What should he use?

A) residual plot
B) normal distribution
C) scatter diagram
D) histogram
E) frequency distribution

Question 10

The _____ measures the linear association between two metric variables, with the number referred to as a correlation coefficient that ranges from -1.00 to +1.00.

A) Pearson correlation
B) Burkett's t
C) scatter diagram
D) Likert correlation
E) Spearman's rho

Question 11

Tim would like to calculate a correlation coefficient to assess the level of association for two metric variables in his database. Tim should use _____.

A) Pearson correlation
B) Burkett's t
C) scatter diagram
D) Likert correlation
E) Spearman's rho

Question 12

The Pearson correlation ranges from _____.

A) -5.00 to +5.00
B) 0 to +1.00
C) -1.00 to + 1.00
D) 1.00 to 2.00
E) 1.00 to 5.00

Question 13

The square of the correlation coefficient is called _____.

A) Pearson correlation
B) Burkett's t
C) coefficient of determination
D) Likert correlation
E) Spearman's rho

Question 14

Which statistic represents the amount of variation explained or accounted for in one variable by one or more other variables, and it is the square of the correlation coefficient?

A) Pearson correlation
B) coefficient of determination
C) Likert correlation
D) Spearman's rho
E) c²

Question 15

Which of the following is the coefficient of determination?

A) β
B) χ²
C) c²
D) F
E) r²

Question 16

Which is NOT an assumption when using the Pearson correlation coefficient?

A) the two variables are assumed to have been measured using metric measures
B) the two variables are assumed to have been measured using nonmetric measures
C) linear relationship
D) normal distribution
E) all of these choices are assumptions when using the Pearson correlation coefficient

Question 17

Which statistic is appropriate for assessing the correlation for nonmetric data?

A) Pearson correlation
B) Spearman's rho
C) Likert correlation
D) c²
E) nonlinear correlation coefficient

Question 18

Sandy wants to examine if gender is related to soft drink consumption. What correlation coefficient is appropriate for this?

A) Pearson correlation
B) Spearman's rho
C) Likert correlation
D) c²
E) nonlinear correlation coefficient

Question 19

Statistical techniques can be divided into two broad categories, which are _____.

A) linear and nonlinear
B) dependence and interdependence
C) dependent and independent
D) exploratory and confirmatory
E) bivariate and multivariate

Question 20

If there is a single dependent variable, a technique is referred to as a _____ method. That is, there are both dependent and independent variables in the analysis.

A) dependence
B) interdependence
C) statistical
D) confirmatory
E) quantitative

Question 21

If all variables are analyzed together and the goal is to form groups or give meaning to a set of variables or respondents, the statistical technique is referred to as a(n) _____ method.

A) dependence
B) interdependence
C) causal
D) quantitative
E) qualitative

Question 22

Which of the following can be used to examine the statistical difference between the means of two or more groups if the dependent variable is metric and the independent variable(s) is nonmetric?

A) ANOVA
B) Spearman's Correlation
C) Cluster analysis
D) Correlation
E) Factor analysis

Question 23

Billy has a dependent variable that is measured with ratio data. All of the following are statistical techniques that would be appropriate for him to use EXCEPT _____.

A) multiple regression
B) ANOVA
C) discriminant analysis
D) correlation analysis
E) all of the above are appropriate

Question 24

This type of regression has a single metric dependent variable and a single metric independent variable.

A) ANOVA
B) Multiple regression
C) Bivariate regression
D) Univariate regression
E) MANOVA regression

Question 25

The _____ method minimizes the distances from the straight line to all the points on a scatter diagram. It measures these distances by looking at the errors in predicting Y from X and minimizes the sum of the squared deviations between the actual values and the straight line predicted by the regression.

A) minimal squares
B) least squares
C) r-squared
D) regression sum of squares
E) residual sum of squares

Question 26

All of the following are assumptions of simple regression EXCEPT _____.

A) linear relationship
B) causality
C) metric measures
D) normally distributed population
E) independent and normally distributed error terms

Question 27

Which of the following assesses the statistical significance of the overall regression model?

A) t statistic
B) Spearman's rho
C) correlation coefficient
D) R²
E) F-ratio

Question 28

Which of the following tell us how much of the variance in the dependent variable is explained by the independent variable in regression?

A) regression coefficient
B) F-ratio
C) t statistic
D) Spearman's rho
E) VIF

Question 29

_____ is a method of adjusting for different units of measure across variables.

A) Multicollinearity
B) Standardization
C) Correlation
D) Coefficient of determination
E) Adjusted R²

Question 30

The proportion of the variability in the dependent variable that can be explained by the several independent variables in the regression model is known as the _____.

A) multiple coefficient of determination
B) standardized beta
C) correlation coefficient
D) Pearson's rho
E) VIF

Question 31

Which of the following is used when you can predict the direction of your hypothesized relationship?

A) unstandardized test
B) standardized test
C) one-tailed test
D) two-tailed test
E) multi-tailed test

Question 32

Frank has hypothesized a relationship between two variables, but he cannot predict the direction of the hypothesized relationship. Which of the following is appropriate in this situation?

A) unstandardized test
B) standardized test
C) one-tailed test
D) two-tailed test
E) multi-tailed test

Question 33

Multicollinearity in multiple regression analysis refers to _____.

A) the correlation among the dependent variables
B) the correlation between the independent and dependent variables
C) level of significance of the model
D) the correlation among the independent variables
E) explained variance

Question 34

Which of the following is NOT a problem caused by multicollinearity in multiple regression?

A) The F-test of the overall multiple regression model may indicate a statistically significant relationship, but the t-tests for the individual coefficients may not indicate any as significant.
B) The regression coefficients can have a sign opposite that of the actual relationship.
C) It impacts the size of the R² and the ability to predict values of the dependent variable.
D) With a high degree of collinearity we cannot rely on the individual coefficients to interpret the results.
E) All of these choices are problems caused by multicollinearity in multiple regression.

Question 35

How does a researcher know when multicollinearity is too high?

A) A sample correlation coefficient between two independent variables is greater than ±0.60.
B) The variance inflation factor equals zero.
C) The variance inflation factor is equal to 1.
D) The tolerance factor is high, such as greater than 1.0
E) The R² is less than 20%.

Question 36

A linear relationship is a straight-line association between two or more variables.

Question 37

Covariation is when one variable consistently and systematically changes relative to another variable.

Question 38

A scatter diagram or scattergram plots the values of a variable for all observations within the sample.

Question 39

A Pearson correlation measures the linear association between two metric variables.

Question 40

The square of the correlation coefficient is called the coefficient of determination or r².

Question 41

Univariate analysis involves statistically testing two variables.

Question 42

Multivariate analysis involves using statistical methods to analyze multiple variables at the same time.

Question 43

Control variables are used to measure the impact of a specific independent variable above and beyond the effects of other independent variables.

Question 44

A one tailed test is used when you cannot predict the direction of the hypothesized relationship.

Question 45

A hierarchical multiple regression is a regression model in which the independent variables are entered in one stage.

Question 46

Explain the relationship between explained and unexplained variance in regression.

Question 47

Name and describe the four basic concepts we need to understand about relationships between variables.

Question 48

Explain the difference between bivariate regression and multiple regression. State the assumptions of both.

Question 49

What is multicollinearity, why is it a problem, and what should a researcher do if it is detected?