Question 1

Which of the following is not true of the linear regression equation?

Accepted Answer

A) It is the equation from which the correlation coefficient is calculated. 
B) It defines the straight line that summarizes a relationship. 
C) It describes two characteristics of the regression line: its slope and its Y-intercept. 
D) It is the equation that produces the value of   at each X. 
A) It is the equation from which the correlation coefficient is calculated. 
B) It defines the straight line that summarizes a relationship. 
C) It describes two characteristics of the regression line: its slope and its Y-intercept. 
D) It is the equation that produces the value of   at each X.

Question 2

Linear regression is important because

Accepted Answer

A) it is used to predict unknown Y scores based on X scores from a correlated variable. 
B) it is used to predict unknown Y scores based on X scores,even if the X variable is not correlated with the Y variable. 
C) it is a statistic that summarizes the relationship between the X and Y variables. 
D) it indicates how close our predictions of Y values are to the actual Y values. 
A) it is used to predict unknown Y scores based on X scores from a correlated variable. 
B) it is used to predict unknown Y scores based on X scores,even if the X variable is not correlated with the Y variable. 
C) it is a statistic that summarizes the relationship between the X and Y variables. 
D) it indicates how close our predictions of Y values are to the actual Y values.

Question 3

The "error" in a single prediction is equal to the degree to which a participant's ______ score deviates from the ______.

Accepted Answer

A) actual;mean 
B) predicted;mean 
C) predicted;given X 
D) actual;corresponding predicted score 
A) actual;mean 
B) predicted;mean 
C) predicted;given X 
D) actual;corresponding predicted score

Question 4

We calculate the proportion of variance accounted for because it is the statistical basis for evaluating

Accepted Answer

A) the usefulness of a relationship. 
B) the strength of the correlation coefficient. 
C) the linearity of the two scores. 
D) the average deviation among the Y scores. 
A) the usefulness of a relationship. 
B) the strength of the correlation coefficient. 
C) the linearity of the two scores. 
D) the average deviation among the Y scores.

Question 5

Homoscedasticity occurs when

Accepted Answer

A) there is a nonlinear relationship between the X and Y scores. 
B) the Y scores have a different degree of spread at different Xs. 
C) the Y scores are spread out to the same degree at every X. 
D) the YF1F1F1S1F1F1F10 scores are spread out to the same degree at every X. 
A) there is a nonlinear relationship between the X and Y scores. 
B) the Y scores have a different degree of spread at different Xs. 
C) the Y scores are spread out to the same degree at every X. 
D) the YF1F1F1S1F1F1F10 scores are spread out to the same degree at every X.

Question 6

In regression,we sometimes talk about using X to predict Y.In such situations,Y is then called

Accepted Answer

A)    
B) the predictor variable. 
C) the criterion variable. 
D) the intercept. 
A)    
B) the predictor variable. 
C) the criterion variable. 
D) the intercept.

Question 7

The slope of a line is a number indicating the

Accepted Answer

A) slant of the line and the Y-intercept. 
B) slant of the line and the direction in which it slants. 
C) slant of the line and the X-intercept. 
D) length of the regression line to be drawn. 
A) slant of the line and the Y-intercept. 
B) slant of the line and the direction in which it slants. 
C) slant of the line and the X-intercept. 
D) length of the regression line to be drawn.

Question 8

The sum of the deviations of the true Y scores from the predicted   scores is always

Accepted Answer

A) zero. 
B) a very large number. 
C) equal to N times the mean of Y. 
D) negative. 
A) zero. 
B) a very large number. 
C) equal to N times the mean of Y. 
D) negative.

Question 9

The linear regression line indicates

Accepted Answer

A) whether a relationship exists. 
B) the strength of a relationship. 
C) the direction of a relationship. 
D) the best-fitting straight line in a linear relationship. 
A) whether a relationship exists. 
B) the strength of a relationship. 
C) the direction of a relationship. 
D) the best-fitting straight line in a linear relationship.

Question 10

In the following study,researchers wanted to determine if a relationship existed between the minutes of light therapy a patient receives and the patient's reported score on a seasonal affective disorder (SAD)test.What is the proportion of variance not accounted for?

Accepted Answer

A) 0.77 
B) 2.31 
C) 0.23 
D) 4.86 
A) 0.77 
B) 2.31 
C) 0.23 
D) 4.86

Question 11

Which of the following is NOT representative of a strong relationship?

Accepted Answer

A) Y scores that are relatively close to their corresponding   scores. 
B) A correlation coefficient close to 1. 
C) Y scores that are spread out. 
D) Less prediction error and a smaller value of   
A) Y scores that are relatively close to their corresponding   scores. 
B) A correlation coefficient close to 1. 
C) Y scores that are spread out. 
D) Less prediction error and a smaller value of

Question 12

Heteroscedasticity occurs when

Accepted Answer

A) there is a nonlinear relationship between the X and Y scores. 
B) the   scores are spread out to the same degree at every X. 
C) the Y scores are spread out to the same degree at every X. 
D) the Y scores have a different degree of spread at different Xs. 
A) there is a nonlinear relationship between the X and Y scores. 
B) the   scores are spread out to the same degree at every X. 
C) the Y scores are spread out to the same degree at every X. 
D) the Y scores have a different degree of spread at different Xs.

Question 13

When we use a relationship to predict scores,our error is

Accepted Answer

A) the mean of Y. 
B) the mean of X. 
C)    . 
D)    . 
A) the mean of Y. 
B) the mean of X. 
C)    . 
D)    .

Question 14

When we square the correlation coefficient to produce   ,the result is equal to the

Accepted Answer

A) proportion of variance not accounted for. 
B) proportion of variance accounted for. 
C) standard error of the estimate. 
D) coefficient of alienation. 
A) proportion of variance not accounted for. 
B) proportion of variance accounted for. 
C) standard error of the estimate. 
D) coefficient of alienation.

Question 15

For the following data,what is the regression equation?

Accepted Answer

A)    = 20.93X - 0.85 
B)    = -0.85 X + 20.93 
C)    = 20.93 X + 0.85 
D)    = 0.85 X + 20.93 
A)    = 20.93X - 0.85 
B)    = -0.85 X + 20.93 
C)    = 20.93 X + 0.85 
D)    = 0.85 X + 20.93

Question 16

is

Accepted Answer

A) the actual Y scores. 
B) the predicted Y scores. 
C) the standard deviation of Y. 
D) the standard error of the estimate. 
A) the actual Y scores. 
B) the predicted Y scores. 
C) the standard deviation of Y. 
D) the standard error of the estimate.

Question 17

In the following study,researchers wanted to determine if a relationship existed between the minutes of light therapy a patient receives and the patient's reported score on a seasonal affective disorder (SAD)test.What is the regression equation for the data below?

Accepted Answer

A)    = -3.08X + 1.64 
B)    = 9.5 X + 12.5 
C)      = 2.69 X - 0.49 
D)      = 1.64 X - 3.08 
A)    = -3.08X + 1.64 
B)    = 9.5 X + 12.5 
C)      = 2.69 X - 0.49 
D)      = 1.64 X - 3.08

Question 18

A recent study of burnout among therapists shows a positive correlation of 0.53 between the number of clients a therapist is treating and the therapist's feelings of burnout.What proportion of the variance in feelings of burnout is accounted for by this relationship?

Accepted Answer

A) 0.73 
B) 0.47 
C) 0.28 
D) 0.53 
A) 0.73 
B) 0.47 
C) 0.28 
D) 0.53

Question 19

In looking at the regression equation,we know that the relationship is negative if the

Accepted Answer

A) Y-intercept value is negative. 
B) slope value is negative. 
C) slope value is zero. 
D) Y-intercept value is zero. 
A) Y-intercept value is negative. 
B) slope value is negative. 
C) slope value is zero. 
D) Y-intercept value is zero.

Question 20

When there is no relationship between two variables,the value of every   is equal to

Accepted Answer

A) the value of every X. 
B) the value of every Y. 
C) the value of the Y-intercept. 
D) zero. 
A) the value of every X. 
B) the value of every Y. 
C) the value of the Y-intercept. 
D) zero.

Which of the following is not true of the linear regression equation?

Linear regression is important because

The "error" in a single prediction is equal to the degree to which a participant's score deviates from the .

We calculate the proportion of variance accounted for because it is the statistical basis for evaluating

Homoscedasticity occurs when

In regression,we sometimes talk about using X to predict Y.In such situations,Y is then called

The slope of a line is a number indicating the

The sum of the deviations of the true Y scores from the predicted scores is always

The linear regression line indicates

In the following study,researchers wanted to determine if a relationship existed between the minutes of light therapy a patient receives and the patient's reported score on a seasonal affective disorder (SAD)test.What is the proportion of variance not accounted for?

Which of the following is NOT representative of a strong relationship?

Heteroscedasticity occurs when

When we use a relationship to predict scores,our error is

When we square the correlation coefficient to produce ,the result is equal to the

For the following data,what is the regression equation?

is

In the following study,researchers wanted to determine if a relationship existed between the minutes of light therapy a patient receives and the patient's reported score on a seasonal affective disorder (SAD)test.What is the regression equation for the data below?

A recent study of burnout among therapists shows a positive correlation of 0.53 between the number of clients a therapist is treating and the therapist's feelings of burnout.What proportion of the variance in feelings of burnout is accounted for by this relationship?

In looking at the regression equation,we know that the relationship is negative if the

When there is no relationship between two variables,the value of every is equal to

Introduction to Statistics

Statistics and the Research Process

Frequency Distributions and Percentiles

Measures of Central Tendency;the Mean, median, and Mode

Measures of Variability: Range, variance, and Standard Deviation

Z-Scores and the Normal Curve

The Correlation Coefficient

Using Probability to Make Decisions About Data

Introduction to Hypothesis Testing

Performing the One-Sample T-Test and Testing Correlation Coefficients

The Two-Sample T-Test

The One-Way Analysis of Variance

The Two-Way Analysis of Variance

Chi Square and Other Nonparametric Procedures

Filters

Exam 8: Linear Regression

Which of the following is not true of the linear regression equation?

Linear regression is important because

The "error" in a single prediction is equal to the degree to which a participant's ______ score deviates from the ______.

We calculate the proportion of variance accounted for because it is the statistical basis for evaluating

Homoscedasticity occurs when

In regression,we sometimes talk about using X to predict Y.In such situations,Y is then called

The slope of a line is a number indicating the

The sum of the deviations of the true Y scores from the predicted scores is always

The linear regression line indicates

In the following study,researchers wanted to determine if a relationship existed between the minutes of light therapy a patient receives and the patient's reported score on a seasonal affective disorder (SAD)test.What is the proportion of variance not accounted for?

Which of the following is NOT representative of a strong relationship?

Heteroscedasticity occurs when

When we use a relationship to predict scores,our error is

When we square the correlation coefficient to produce ,the result is equal to the

For the following data,what is the regression equation?

is

In the following study,researchers wanted to determine if a relationship existed between the minutes of light therapy a patient receives and the patient's reported score on a seasonal affective disorder (SAD)test.What is the regression equation for the data below?

A recent study of burnout among therapists shows a positive correlation of 0.53 between the number of clients a therapist is treating and the therapist's feelings of burnout.What proportion of the variance in feelings of burnout is accounted for by this relationship?

In looking at the regression equation,we know that the relationship is negative if the

When there is no relationship between two variables,the value of every is equal to

Introduction to Statistics

Statistics and the Research Process

Frequency Distributions and Percentiles

Measures of Central Tendency;the Mean, median, and Mode

Measures of Variability: Range, variance, and Standard Deviation

Z-Scores and the Normal Curve

The Correlation Coefficient

Using Probability to Make Decisions About Data

Introduction to Hypothesis Testing

Performing the One-Sample T-Test and Testing Correlation Coefficients

The Two-Sample T-Test

The One-Way Analysis of Variance

The Two-Way Analysis of Variance

Chi Square and Other Nonparametric Procedures

Filters

The "error" in a single prediction is equal to the degree to which a participant's score deviates from the .