Question 1

In a regression equation,the variable being predicted (or _____)is known as a(n)_______ variable.

Accepted Answer

A) X;dependent or criterion 
B) X;independent or predictor 
C) Y;dependent or criterion 
D) Y;independent or predictor 
A) X;dependent or criterion 
B) X;independent or predictor 
C) Y;dependent or criterion 
D) Y;independent or predictor

Question 2

A relationship might exist in a sample even though it does not exist in the population,because of:

Accepted Answer

A) idiosyncratic variance 
B) incorrect inference 
C) confounding variables 
D) sampling error 
A) idiosyncratic variance 
B) incorrect inference 
C) confounding variables 
D) sampling error

Question 3

The mean of a sampling distribution of r is approximately equal to r.

Accepted Answer

A) True 
 B)False

Question 4

The strength of the relationship between two variables in a correlational analysis can be represented by:

Accepted Answer

A) eta-squared 
B) r2 
C) eta-squared and r2 
D) t2 and F2 
A) eta-squared 
B) r2 
C) eta-squared and r2 
D) t2 and F2

Question 5

Which of the following is NOT one of the assumptions of the Pearson correlation?

Accepted Answer

A) The sample is independently and randomly selected from the population. 
B) The variances of the Y scores are equal at every value of X in the population. 
C) The variables X and Y are qualitative in nature. 
D) The joint distribution (or scatterplot)of X and Y represent a bivariate normal distribution. 
A) The sample is independently and randomly selected from the population. 
B) The variances of the Y scores are equal at every value of X in the population. 
C) The variables X and Y are qualitative in nature. 
D) The joint distribution (or scatterplot)of X and Y represent a bivariate normal distribution.

Question 6

Perfect linear relationships between Y and X are relatively common in the behavioral sciences.

Accepted Answer

A) True 
 B)False

Question 7

Because the calculation of t depends only on the value of r,it is impossible to determine
values of r that will lead to a rejection of the null hypothesis that ñ = 0,given a certain
sample size.

Accepted Answer

A) True 
 B)False

Question 8

In the context of regression,the variable being predicted,Y,is formally known as the dependent or _____ variable;the variable from which predictions are made,X ,is formally known as the independent or _____ variable.

Accepted Answer

A) confounding;disturbance 
B) exogenous;predictor 
C) criterion;predictor 
D) predictor;criterion 
A) confounding;disturbance 
B) exogenous;predictor 
C) criterion;predictor 
D) predictor;criterion

Question 9

The slope indicates the number of units Y is predicted to change given a one unit change in X.

Accepted Answer

A) True 
 B)False

Question 10

The variable being predicted,Y,is formally known as the dependent or criterion variable.

Accepted Answer

A) True 
 B)False

Question 11

The value of r2 represents the proportion of variability _____.

Accepted Answer

A) in the dependent variable that is associated with the independent variable 
B) that is due to disturbance variables 
C) that is unaccounted for 
A) in the dependent variable that is associated with the independent variable 
B) that is due to disturbance variables 
C) that is unaccounted for

Question 12

The nature of the relationship between two correlated variables is determined through
examination of the sign of the correlation coefficient observed in the sample.

Accepted Answer

A) True 
 B)False

Question 13

How is the nature of the relationship between two variables evaluated in a correlational analysis?

Accepted Answer

The nature of the relationship between t

Question 14

In the context of regression,prediction merely refers to the fact that we are making
inferences about one variable from a second variable and does not imply that the latter
variable causes the former.

Accepted Answer

A) True 
 B)False

Question 15

Variance heterogeneity can be problematic for the t test of the Pearson correlation coefficient,especially if one is going to pursue estimation of the:

Accepted Answer

A) population variance 
B) sample correlation coefficient 
C) population regression equation 
D) population mean 
A) population variance 
B) sample correlation coefficient 
C) population regression equation 
D) population mean

Question 16

The Pearson correlation technique may be used to measure _____ relationships when both X and Y are _____ in nature.

Accepted Answer

A) curvilinear;qualitative 
B) linear;qualitative 
C) linear;quantitative 
D) curvilinear;quantitative 
A) curvilinear;qualitative 
B) linear;qualitative 
C) linear;quantitative 
D) curvilinear;quantitative

Question 17

Imagine you are interested in researching the relationship between job experience and income among early-career working professionals.You take a random sample of 32 professionals from the nearest city,and you ask them to report their annual income and submit a resumé outlining their professional experience.You later calculate their years of experience from their resumés.You compute the following information:  
After comparing the observed correlation to the critical values of $\pm$2.042,what would your conclusion be regarding the "true" correlation in the population (r)?

Accepted Answer

A) r most likely differed from zero because of sampling error 
B) You are confident that r does not equal zero 
C) It is likely that r1 ¹ r2 
D) There is a weak relationship between work experience and income 
A) r most likely differed from zero because of sampling error 
B) You are confident that r does not equal zero 
C) It is likely that r1 ¹ r2 
D) There is a weak relationship between work experience and income

Question 18

If we find a high correlation between variables X and Y,we can conclude _____.

Accepted Answer

A) X causes Y 
B) Y causes X 
C) X and Y have the same cause 
D) X and Y systematically vary together 
A) X causes Y 
B) Y causes X 
C) X and Y have the same cause 
D) X and Y systematically vary together

Question 19

The variable from which predictions are made,X,is formally known as the independent or predictor variable.

Accepted Answer

A) True 
 B)False

Question 20

The strength of the relationship in a correlational analysis can be calculated with

Accepted Answer

A) a ratio of explained variability to total variability. 
B) r2 
C) the coefficient of determination 
D) both a and b 
E) all of these 
A) a ratio of explained variability to total variability. 
B) r2 
C) the coefficient of determination 
D) both a and b 
E) all of these

In a regression equation,the variable being predicted (or _)is known as a(n)___ variable.

A relationship might exist in a sample even though it does not exist in the population,because of:

The mean of a sampling distribution of r is approximately equal to r.

The strength of the relationship between two variables in a correlational analysis can be represented by:

Which of the following is NOT one of the assumptions of the Pearson correlation?

Perfect linear relationships between Y and X are relatively common in the behavioral sciences.

Because the calculation of t depends only on the value of r,it is impossible to determine values of r that will lead to a rejection of the null hypothesis that ñ = 0,given a certain sample size.

In the context of regression,the variable being predicted,Y,is formally known as the dependent or _ variable;the variable from which predictions are made,X ,is formally known as the independent or _ variable.

The slope indicates the number of units Y is predicted to change given a one unit change in X.

The variable being predicted,Y,is formally known as the dependent or criterion variable.

The value of r² represents the proportion of variability _____.

The nature of the relationship between two correlated variables is determined through examination of the sign of the correlation coefficient observed in the sample.

How is the nature of the relationship between two variables evaluated in a correlational analysis?

In the context of regression,prediction merely refers to the fact that we are making inferences about one variable from a second variable and does not imply that the latter variable causes the former.

Variance heterogeneity can be problematic for the t test of the Pearson correlation coefficient,especially if one is going to pursue estimation of the:

The Pearson correlation technique may be used to measure _ relationships when both X and Y are _ in nature.

If we find a high correlation between variables X and Y,we can conclude _____.

The variable from which predictions are made,X,is formally known as the independent or predictor variable.

The strength of the relationship in a correlational analysis can be calculated with

Introduction and Mathematical Preliminaries

Frequency and Probability Distributions

Measures of Central Tendency and Variability

Percentiles,percentile Ranks,standard Scores,and the Normal Distribution

Pearson Correlation and Regression: Descriptive Aspects

Probability

Estimation and Sampling Distributions

Hypothesis Testing: Inferences About a Single Mean

Principles of Research Design and Statistical Preliminaries for Analyzing Bivariate Relationships

Independent Groups T-Test

Correlated Groups T-Test

One-Way Repeated Measures Analysis of Variance

Chi-Square Test

Nonparametric Statistics

Two-Way Between-Subjects Analysis of Variance

Overview and Extension: Statistical Tests for More Complex Designs

Filters

Exam 13: Pearson Correlation and Regression: Inferential Aspects

In a regression equation,the variable being predicted (or _____)is known as a(n)_______ variable.

A relationship might exist in a sample even though it does not exist in the population,because of:

The mean of a sampling distribution of r is approximately equal to r.

The strength of the relationship between two variables in a correlational analysis can be represented by:

Which of the following is NOT one of the assumptions of the Pearson correlation?

Perfect linear relationships between Y and X are relatively common in the behavioral sciences.

Because the calculation of t depends only on the value of r,it is impossible to determine values of r that will lead to a rejection of the null hypothesis that ñ = 0,given a certain sample size.

In the context of regression,the variable being predicted,Y,is formally known as the dependent or _____ variable;the variable from which predictions are made,X ,is formally known as the independent or _____ variable.

The slope indicates the number of units Y is predicted to change given a one unit change in X.

The variable being predicted,Y,is formally known as the dependent or criterion variable.

The value of r2 represents the proportion of variability _____.

The nature of the relationship between two correlated variables is determined through examination of the sign of the correlation coefficient observed in the sample.

How is the nature of the relationship between two variables evaluated in a correlational analysis?

In the context of regression,prediction merely refers to the fact that we are making inferences about one variable from a second variable and does not imply that the latter variable causes the former.

Variance heterogeneity can be problematic for the t test of the Pearson correlation coefficient,especially if one is going to pursue estimation of the:

The Pearson correlation technique may be used to measure _____ relationships when both X and Y are _____ in nature.

If we find a high correlation between variables X and Y,we can conclude _____.

The variable from which predictions are made,X,is formally known as the independent or predictor variable.

The strength of the relationship in a correlational analysis can be calculated with

Introduction and Mathematical Preliminaries

Frequency and Probability Distributions

Measures of Central Tendency and Variability

Percentiles,percentile Ranks,standard Scores,and the Normal Distribution

Pearson Correlation and Regression: Descriptive Aspects

Probability

Estimation and Sampling Distributions

Hypothesis Testing: Inferences About a Single Mean

Principles of Research Design and Statistical Preliminaries for Analyzing Bivariate Relationships

Independent Groups T-Test

Correlated Groups T-Test

One-Way Repeated Measures Analysis of Variance

Chi-Square Test

Nonparametric Statistics

Two-Way Between-Subjects Analysis of Variance

Overview and Extension: Statistical Tests for More Complex Designs

Filters

In a regression equation,the variable being predicted (or _)is known as a(n)___ variable.

In the context of regression,the variable being predicted,Y,is formally known as the dependent or _ variable;the variable from which predictions are made,X ,is formally known as the independent or _ variable.

The value of r² represents the proportion of variability _____.

The Pearson correlation technique may be used to measure _ relationships when both X and Y are _ in nature.