Deck 8: Linear Regression

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

A) <strong>In regression,we sometimes talk about using X to predict Y.In such situations,Y is then called</strong> A)   B)the predictor variable. C)the criterion variable. D)the intercept. <div style=padding-top: 35px>
B)the predictor variable.
C)the criterion variable.
D)the intercept.
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Question
A regression line is used to obtain

A)the Y at each X.
B)the X at each Y.
C)the <strong>A regression line is used to obtain</strong> A)the Y at each X. B)the X at each Y. C)the   at any X. D)the X at any   . <div style=padding-top: 35px> at any X.
D)the X at any <strong>A regression line is used to obtain</strong> A)the Y at each X. B)the X at each Y. C)the   at any X. D)the X at any   . <div style=padding-top: 35px> .
Question
What is the slope of the following regression equation? <strong>What is the slope of the following regression equation?  </strong> A)3.92 B)-3.92 C)2.69 D)2.69X <div style=padding-top: 35px>

A)3.92
B)-3.92
C)2.69
D)2.69X
Question
The linear regression line indicates

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
The slope of a line is a number indicating the

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
Linear regression is important because

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
The best-fitting line through a scatterplot is known as the ______ line.

A)scatterplot
B)correlation
C)variance
D)regression
Question
Which of the following formulas represents the Y intercept of the regression line?

A) <strong>Which of the following formulas represents the Y intercept of the regression line?</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
B) <strong>Which of the following formulas represents the Y intercept of the regression line?</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
C) <strong>Which of the following formulas represents the Y intercept of the regression line?</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
D) <strong>Which of the following formulas represents the Y intercept of the regression line?</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
Question
Which of the following is not true of the linear regression equation?

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 <strong>Which of the following is not true of the linear regression equation?</strong> 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. <div style=padding-top: 35px> at each X.
Question
What is the Y-intercept of the following regression equation? <strong>What is the Y-intercept of the following regression equation?  </strong> A)0.56X B)0.56 C)2.41 D)X + 2.41 <div style=padding-top: 35px>

A)0.56X
B)0.56
C)2.41
D)X + 2.41
Question
In the regression equation,the slope summarizes ______ and the Y-intercept indicates ______.

A)predictor variables;what the value of the criterion variable is
B)the steepness and direction of the regression line;the value of <strong>In the regression equation,the slope summarizes ______ and the Y-intercept indicates ______.</strong> A)predictor variables;what the value of the criterion variable is B)the steepness and direction of the regression line;the value of   when X = 0 C)the length of the regression line;the starting point of the regression line D)the starting point from which the Y scores begin to change as the X scores increase;the direction and rate in which Ys change as X increases <div style=padding-top: 35px> when X = 0
C)the length of the regression line;the starting point of the regression line
D)the starting point from which the Y scores begin to change as the X scores increase;the direction and rate in which Ys change as X increases
Question
What is the Y-intercept of the following regression equation? <strong>What is the Y-intercept of the following regression equation?   = -4.30X - 1.72</strong> A)-1.72 B)1.72 C)-4.30 D)-4.30X <div style=padding-top: 35px> = -4.30X - 1.72

A)-1.72
B)1.72
C)-4.30
D)-4.30X
Question
The regression line is the best-fitting line because

A)it best takes into account all the X and Y scores.
B)on average,the regression line passes through the center of the various Y standard deviations.
C)it is the straightest line that can be created through the Y scores.
D)on average,the regression line passes through the center of the various Y means.
Question
In looking at the regression equation,we know that the relationship is negative if the

A)Y-intercept value is negative.
B)slope value is negative.
C)slope value is zero.
D)Y-intercept value is zero.
Question
What is the slope of the following regression equation? <strong>What is the slope of the following regression equation?   = -8.27X + 3.09</strong> A)8.27 B)-8.27 C)3.09 D)-3.09 <div style=padding-top: 35px> = -8.27X + 3.09

A)8.27
B)-8.27
C)3.09
D)-3.09
Question
The Y-intercept is the value of <strong>The Y-intercept is the value of   when X equals</strong> A)1.0 B)0.0 C)-1.0 D)2.0 <div style=padding-top: 35px> when X equals

A)1.0
B)0.0
C)-1.0
D)2.0
Question
Which of the following is NOT representative of a strong relationship?

A)Y scores that are relatively close to their corresponding <strong>Which of the following is NOT representative of a strong relationship?</strong> 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   <div style=padding-top: 35px> scores.
B)A correlation coefficient close to 1.
C)Y scores that are spread out.
D)Less prediction error and a smaller value of <strong>Which of the following is NOT representative of a strong relationship?</strong> 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   <div style=padding-top: 35px>
Question
Which of the following formulas represents the slope of the regression line?

A) <strong>Which of the following formulas represents the slope of the regression line?</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
B) <strong>Which of the following formulas represents the slope of the regression line?</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
C) <strong>Which of the following formulas represents the slope of the regression line?</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
D) <strong>Which of the following formulas represents the slope of the regression line?</strong> A)   B)   C)   D)   <div style=padding-top: 35px>
Question
<strong>  is</strong> A)the actual Y scores. B)the predicted Y scores. C)the standard deviation of Y. D)the standard error of the estimate. <div style=padding-top: 35px> is

A)the actual Y scores.
B)the predicted Y scores.
C)the standard deviation of Y.
D)the standard error of the estimate.
Question
If there is no relationship between two variables,the slope of the regression line will equal

A)1.0
B)0.5
C)0.0
D)-1.0
Question
For the following data,what is the predicted test score for a person with a stress level of 10? <strong>For the following data,what is the predicted test score for a person with a stress level of 10?  </strong> A)0.76 B)20.93 C)-7.16 D)12.43 <div style=padding-top: 35px>

A)0.76
B)20.93
C)-7.16
D)12.43
Question
One assumption of linear regression is

A)the Y scores at each X form an approximately normal distribution.
B)the X scores at each Y form an approximately normal distribution.
C)at each X,both the X and Y score samples should represent an approximately normal distribution.
D)at each X,approximately 68% of all Y scores should be between <strong>One assumption of linear regression is</strong> A)the Y scores at each X form an approximately normal distribution. B)the X scores at each Y form an approximately normal distribution. C)at each X,both the X and Y score samples should represent an approximately normal distribution. D)at each X,approximately 68% of all Y scores should be between   . <div style=padding-top: 35px> .
Question
For the following data,what is the standard error of the estimate? <strong>For the following data,what is the standard error of the estimate?  </strong> A)3.71 B)5.72 C)32.72 D)1,070.49 <div style=padding-top: 35px>

A)3.71
B)5.72
C)32.72
D)1,070.49
Question
For the following data,what is the regression equation? <strong>For the following data,what is the regression equation?  </strong> A)   = 20.93X - 0.85 B)   = -0.85 X + 20.93 C)   = 20.93 X + 0.85 D)   = 0.85 X + 20.93 <div style=padding-top: 35px>

A) <strong>For the following data,what is the regression equation?  </strong> A)   = 20.93X - 0.85 B)   = -0.85 X + 20.93 C)   = 20.93 X + 0.85 D)   = 0.85 X + 20.93 <div style=padding-top: 35px> = 20.93X - 0.85
B) <strong>For the following data,what is the regression equation?  </strong> A)   = 20.93X - 0.85 B)   = -0.85 X + 20.93 C)   = 20.93 X + 0.85 D)   = 0.85 X + 20.93 <div style=padding-top: 35px> = -0.85 X + 20.93
C) <strong>For the following data,what is the regression equation?  </strong> A)   = 20.93X - 0.85 B)   = -0.85 X + 20.93 C)   = 20.93 X + 0.85 D)   = 0.85 X + 20.93 <div style=padding-top: 35px> = 20.93 X + 0.85
D) <strong>For the following data,what is the regression equation?  </strong> A)   = 20.93X - 0.85 B)   = -0.85 X + 20.93 C)   = 20.93 X + 0.85 D)   = 0.85 X + 20.93 <div style=padding-top: 35px> = 0.85 X + 20.93
Question
The sum of the deviations of the true Y scores from the predicted <strong>The sum of the deviations of the true Y scores from the predicted   scores is always</strong> A)zero. B)a very large number. C)equal to N times the mean of Y. D)negative. <div style=padding-top: 35px> scores is always

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

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 Y' scores are spread out to the same degree at every X.
Question
A nutrition major at State University was studying the relationship between carbohydrates (X)and calories (Y).For example,a serving of a particular brand of wheat pasta yielded 42 carbohydrates and 210 calories.After collecting X and Y data on many kinds of foods,the student determined the slope of the regression line to be 4.0 and the Y intercept to be 3.0.If a new food is tested,and the number of carbohydrates (X)is 100,what would be the predicted calories ( <strong>A nutrition major at State University was studying the relationship between carbohydrates (X)and calories (Y).For example,a serving of a particular brand of wheat pasta yielded 42 carbohydrates and 210 calories.After collecting X and Y data on many kinds of foods,the student determined the slope of the regression line to be 4.0 and the Y intercept to be 3.0.If a new food is tested,and the number of carbohydrates (X)is 100,what would be the predicted calories (   )?</strong> A)304 B)403 C)305 D)504 <div style=padding-top: 35px> )?

A)304
B)403
C)305
D)504
Question
If the correlation coefficient turns out to be a relatively high value,then the value of <strong>If the correlation coefficient turns out to be a relatively high value,then the value of   will be</strong> A)relatively low. B)relatively high. C)unrelated to the value of r. D)low if r is positive and high if r is negative. <div style=padding-top: 35px> will be

A)relatively low.
B)relatively high.
C)unrelated to the value of r.
D)low if r is positive and high if r is negative.
Question
The standard error of the estimate is similar to the

A)sum of the actual Y scores around their predicted Y' scores.
B)standard deviation of actual Y scores around their predicted Y' scores.
C)degree to which any predicted Y' will deviate from its actual Y score.
D)standard deviation of actual Y scores around their actual X scores.
Question
The "error" in a single prediction is equal to the degree to which a participant's ______ score deviates from the ______.

A)actual;mean
B)predicted;mean
C)predicted;given X
D)actual;corresponding predicted score
Question
In a study of the relationship between amount of sugar consumed (X)and excitability (Y)in children,the regression equation was calculated to be <strong>In a study of the relationship between amount of sugar consumed (X)and excitability (Y)in children,the regression equation was calculated to be   .The amount of sugar consumed ranged from 1 to 4 ounces.Which of the following graphs correctly displays the regression line?  </strong> A)Graph A B)Graph B C)Graph C D)Graph D <div style=padding-top: 35px> .The amount of sugar consumed ranged from 1 to 4 ounces.Which of the following graphs correctly displays the regression line? <strong>In a study of the relationship between amount of sugar consumed (X)and excitability (Y)in children,the regression equation was calculated to be   .The amount of sugar consumed ranged from 1 to 4 ounces.Which of the following graphs correctly displays the regression line?  </strong> A)Graph A B)Graph B C)Graph C D)Graph D <div style=padding-top: 35px>

A)Graph A
B)Graph B
C)Graph C
D)Graph D
Question
To predict a <strong>To predict a   score from a given X score using the regression equation,we would</strong> A)first multiply X by the slope and then add the Y-intercept. B)first multiply X by the Y-intercept and then add the slope. C)first add the Y-intercept to X and then multiply by the slope. D)first add the slope to X and then multiply by the Y-intercept. <div style=padding-top: 35px> score from a given X score using the regression equation,we would

A)first multiply X by the slope and then add the Y-intercept.
B)first multiply X by the Y-intercept and then add the slope.
C)first add the Y-intercept to X and then multiply by the slope.
D)first add the slope to X and then multiply by the Y-intercept.
Question
When heteroscedasticity exists,the problem with r is that it

A)does not accurately describe the predicted Y values.
B)is very large.
C)does not accurately describe the strength of the relationship for all Xs.
D)will equal 0.
Question
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? <strong>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?  </strong> A)   = -3.08X + 1.64 B)   = 9.5 X + 12.5 C)   <sup> </sup> = 2.69 X - 0.49 D)   <sup> </sup> = 1.64 X - 3.08 <div style=padding-top: 35px>

A) <strong>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?  </strong> A)   = -3.08X + 1.64 B)   = 9.5 X + 12.5 C)   <sup> </sup> = 2.69 X - 0.49 D)   <sup> </sup> = 1.64 X - 3.08 <div style=padding-top: 35px> = -3.08X + 1.64
B) <strong>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?  </strong> A)   = -3.08X + 1.64 B)   = 9.5 X + 12.5 C)   <sup> </sup> = 2.69 X - 0.49 D)   <sup> </sup> = 1.64 X - 3.08 <div style=padding-top: 35px> = 9.5 X + 12.5
C) <strong>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?  </strong> A)   = -3.08X + 1.64 B)   = 9.5 X + 12.5 C)   <sup> </sup> = 2.69 X - 0.49 D)   <sup> </sup> = 1.64 X - 3.08 <div style=padding-top: 35px> = 2.69 X - 0.49
D) <strong>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?  </strong> A)   = -3.08X + 1.64 B)   = 9.5 X + 12.5 C)   <sup> </sup> = 2.69 X - 0.49 D)   <sup> </sup> = 1.64 X - 3.08 <div style=padding-top: 35px> = 1.64 X - 3.08
Question
Heteroscedasticity occurs when

A)there is a nonlinear relationship between the X and Y scores.
B)the <strong>Heteroscedasticity occurs when</strong> 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. <div style=padding-top: 35px> 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
Computing the standard error of the estimate ( <strong>Computing the standard error of the estimate (   )by subtracting each   from the corresponding Y,squaring the difference,summing the results,dividing by N,and then taking the square root (the defining formula)is difficult and time-consuming.Fortunately,the same value can be computed by multiplying the standard deviation of Y (i.e. ,   )by</strong> A)100 B)   C)   D)0.5 <div style=padding-top: 35px> )by subtracting each <strong>Computing the standard error of the estimate (   )by subtracting each   from the corresponding Y,squaring the difference,summing the results,dividing by N,and then taking the square root (the defining formula)is difficult and time-consuming.Fortunately,the same value can be computed by multiplying the standard deviation of Y (i.e. ,   )by</strong> A)100 B)   C)   D)0.5 <div style=padding-top: 35px> from the corresponding Y,squaring the difference,summing the results,dividing by N,and then taking the square root (the defining formula)is difficult and time-consuming.Fortunately,the same value can be computed by multiplying the standard deviation of Y (i.e. , <strong>Computing the standard error of the estimate (   )by subtracting each   from the corresponding Y,squaring the difference,summing the results,dividing by N,and then taking the square root (the defining formula)is difficult and time-consuming.Fortunately,the same value can be computed by multiplying the standard deviation of Y (i.e. ,   )by</strong> A)100 B)   C)   D)0.5 <div style=padding-top: 35px> )by

A)100
B) <strong>Computing the standard error of the estimate (   )by subtracting each   from the corresponding Y,squaring the difference,summing the results,dividing by N,and then taking the square root (the defining formula)is difficult and time-consuming.Fortunately,the same value can be computed by multiplying the standard deviation of Y (i.e. ,   )by</strong> A)100 B)   C)   D)0.5 <div style=padding-top: 35px>
C) <strong>Computing the standard error of the estimate (   )by subtracting each   from the corresponding Y,squaring the difference,summing the results,dividing by N,and then taking the square root (the defining formula)is difficult and time-consuming.Fortunately,the same value can be computed by multiplying the standard deviation of Y (i.e. ,   )by</strong> A)100 B)   C)   D)0.5 <div style=padding-top: 35px>
D)0.5
Question
When r = 1.0,then <strong>When r = 1.0,then   equals</strong> A)r B)0 C)1.0 D)   <div style=padding-top: 35px> equals

A)r
B)0
C)1.0
D) <strong>When r = 1.0,then   equals</strong> A)r B)0 C)1.0 D)   <div style=padding-top: 35px>
Question
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 standard error of the estimate? <strong>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 standard error of the estimate?  </strong> A)2.31 B)4.86 C)5.34 D)1.52 <div style=padding-top: 35px>

A)2.31
B)4.86
C)5.34
D)1.52
Question
When there is no relationship between two variables,the value of every <strong>When there is no relationship between two variables,the value of every   is equal to</strong> A)the value of every X. B)the value of every Y. C)the value of the Y-intercept. D)zero. <div style=padding-top: 35px> is equal to

A)the value of every X.
B)the value of every Y.
C)the value of the Y-intercept.
D)zero.
Question
When r = 0.0,the value of <strong>When r = 0.0,the value of   is equal to</strong> A)   B)0 C)1.0 D)   <div style=padding-top: 35px> is equal to

A) <strong>When r = 0.0,the value of   is equal to</strong> A)   B)0 C)1.0 D)   <div style=padding-top: 35px>
B)0
C)1.0
D) <strong>When r = 0.0,the value of   is equal to</strong> A)   B)0 C)1.0 D)   <div style=padding-top: 35px>
Question
The coefficient of alienation is interpreted as the

A)amount of variance determined in all the Y scores.
B)alienation of variance in all the Y scores.
C)degree to which the scores are efficient.
D)proportion of variance not accounted for.
Question
When we square the correlation coefficient to produce <strong>When we square the correlation coefficient to produce   ,the result is equal to the</strong> A)proportion of variance not accounted for. B)proportion of variance accounted for. C)standard error of the estimate. D)coefficient of alienation. <div style=padding-top: 35px> ,the result is equal to the

A)proportion of variance not accounted for.
B)proportion of variance accounted for.
C)standard error of the estimate.
D)coefficient of alienation.
Question
We calculate the proportion of variance accounted for because it is the statistical basis for evaluating

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
The coefficient of determination is interpreted as the

A)amount of variance determined in all the Y scores.
B)determined amount of variance in all the Y scores.
C)degree to which the scores are efficient.
D)proportion of variance accounted for.
Question
For the following data,what is the proportion of variance accounted for? <strong>For the following data,what is the proportion of variance accounted for?  </strong> A)-0.76 B)0.58 C)0.76 D)-0.58 <div style=padding-top: 35px>

A)-0.76
B)0.58
C)0.76
D)-0.58
Question
When we use a relationship to predict scores,our error is

A)the mean of Y.
B)the mean of X.
C) <strong>When we use a relationship to predict scores,our error is</strong> A)the mean of Y. B)the mean of X. C)   . D)   . <div style=padding-top: 35px> .
D) <strong>When we use a relationship to predict scores,our error is</strong> A)the mean of Y. B)the mean of X. C)   . D)   . <div style=padding-top: 35px> .
Question
In general,the greater the proportion of variance accounted for,

A)the more error there is in the data.
B)the less accurately we can predict behavior.
C)the more accurately we can predict behavior.
D)the less important the relationship to our ability to make predictions.
Question
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?

A)0.73
B)0.47
C)0.28
D)0.53
Question
Compared to a strong relationship,a weak relationship between two variables results in

A)greater prediction error and a larger value of <strong>Compared to a strong relationship,a weak relationship between two variables results in</strong> A)greater prediction error and a larger value of   . B)greater prediction error and a smaller value of   . C)less prediction error and a larger value of   . D)less<sub> </sub>prediction error and a smaller value of   . <div style=padding-top: 35px> .
B)greater prediction error and a smaller value of <strong>Compared to a strong relationship,a weak relationship between two variables results in</strong> A)greater prediction error and a larger value of   . B)greater prediction error and a smaller value of   . C)less prediction error and a larger value of   . D)less<sub> </sub>prediction error and a smaller value of   . <div style=padding-top: 35px> .
C)less prediction error and a larger value of <strong>Compared to a strong relationship,a weak relationship between two variables results in</strong> A)greater prediction error and a larger value of   . B)greater prediction error and a smaller value of   . C)less prediction error and a larger value of   . D)less<sub> </sub>prediction error and a smaller value of   . <div style=padding-top: 35px> .
D)less prediction error and a smaller value of <strong>Compared to a strong relationship,a weak relationship between two variables results in</strong> A)greater prediction error and a larger value of   . B)greater prediction error and a smaller value of   . C)less prediction error and a larger value of   . D)less<sub> </sub>prediction error and a smaller value of   . <div style=padding-top: 35px> .
Question
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? <strong>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?  </strong> A)0.77 B)2.31 C)0.23 D)4.86 <div style=padding-top: 35px>

A)0.77
B)2.31
C)0.23
D)4.86
Question
The coefficient of determination is equal to

A) <strong>The coefficient of determination is equal to</strong> A)   . B)   . C)   . D)   <div style=padding-top: 35px> .
B) <strong>The coefficient of determination is equal to</strong> A)   . B)   . C)   . D)   <div style=padding-top: 35px> .
C) <strong>The coefficient of determination is equal to</strong> A)   . B)   . C)   . D)   <div style=padding-top: 35px> .
D) <strong>The coefficient of determination is equal to</strong> A)   . B)   . C)   . D)   <div style=padding-top: 35px>
Question
When we divide the error remaining after we use the relationship to predict Y scores ( <strong>When we divide the error remaining after we use the relationship to predict Y scores (   )by the total error when we use the mean to predict the Y scores (   )and then subtract the result from 1,the final result is the</strong> A)proportion of variance not accounted for. B)proportion of variance accounted for. C)standard error of the estimate. D)coefficient of alienation. <div style=padding-top: 35px> )by the total error when we use the mean to predict the Y scores ( <strong>When we divide the error remaining after we use the relationship to predict Y scores (   )by the total error when we use the mean to predict the Y scores (   )and then subtract the result from 1,the final result is the</strong> A)proportion of variance not accounted for. B)proportion of variance accounted for. C)standard error of the estimate. D)coefficient of alienation. <div style=padding-top: 35px> )and then subtract the result from 1,the final result is the

A)proportion of variance not accounted for.
B)proportion of variance accounted for.
C)standard error of the estimate.
D)coefficient of alienation.
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Deck 8: Linear Regression
1
In regression,we sometimes talk about using X to predict Y.In such situations,Y is then called

A) <strong>In regression,we sometimes talk about using X to predict Y.In such situations,Y is then called</strong> A)   B)the predictor variable. C)the criterion variable. D)the intercept.
B)the predictor variable.
C)the criterion variable.
D)the intercept.
the criterion variable.
2
A regression line is used to obtain

A)the Y at each X.
B)the X at each Y.
C)the <strong>A regression line is used to obtain</strong> A)the Y at each X. B)the X at each Y. C)the   at any X. D)the X at any   . at any X.
D)the X at any <strong>A regression line is used to obtain</strong> A)the Y at each X. B)the X at each Y. C)the   at any X. D)the X at any   . .
the the   at any X. at any X.
3
What is the slope of the following regression equation? <strong>What is the slope of the following regression equation?  </strong> A)3.92 B)-3.92 C)2.69 D)2.69X

A)3.92
B)-3.92
C)2.69
D)2.69X
2.69
4
The linear regression line indicates

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.
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5
The slope of a line is a number indicating the

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.
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6
Linear regression is important because

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.
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7
The best-fitting line through a scatterplot is known as the ______ line.

A)scatterplot
B)correlation
C)variance
D)regression
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8
Which of the following formulas represents the Y intercept of the regression line?

A) <strong>Which of the following formulas represents the Y intercept of the regression line?</strong> A)   B)   C)   D)
B) <strong>Which of the following formulas represents the Y intercept of the regression line?</strong> A)   B)   C)   D)
C) <strong>Which of the following formulas represents the Y intercept of the regression line?</strong> A)   B)   C)   D)
D) <strong>Which of the following formulas represents the Y intercept of the regression line?</strong> A)   B)   C)   D)
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9
Which of the following is not true of the linear regression equation?

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 <strong>Which of the following is not true of the linear regression equation?</strong> 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. at each X.
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10
What is the Y-intercept of the following regression equation? <strong>What is the Y-intercept of the following regression equation?  </strong> A)0.56X B)0.56 C)2.41 D)X + 2.41

A)0.56X
B)0.56
C)2.41
D)X + 2.41
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11
In the regression equation,the slope summarizes ______ and the Y-intercept indicates ______.

A)predictor variables;what the value of the criterion variable is
B)the steepness and direction of the regression line;the value of <strong>In the regression equation,the slope summarizes ______ and the Y-intercept indicates ______.</strong> A)predictor variables;what the value of the criterion variable is B)the steepness and direction of the regression line;the value of   when X = 0 C)the length of the regression line;the starting point of the regression line D)the starting point from which the Y scores begin to change as the X scores increase;the direction and rate in which Ys change as X increases when X = 0
C)the length of the regression line;the starting point of the regression line
D)the starting point from which the Y scores begin to change as the X scores increase;the direction and rate in which Ys change as X increases
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12
What is the Y-intercept of the following regression equation? <strong>What is the Y-intercept of the following regression equation?   = -4.30X - 1.72</strong> A)-1.72 B)1.72 C)-4.30 D)-4.30X = -4.30X - 1.72

A)-1.72
B)1.72
C)-4.30
D)-4.30X
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13
The regression line is the best-fitting line because

A)it best takes into account all the X and Y scores.
B)on average,the regression line passes through the center of the various Y standard deviations.
C)it is the straightest line that can be created through the Y scores.
D)on average,the regression line passes through the center of the various Y means.
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14
In looking at the regression equation,we know that the relationship is negative if the

A)Y-intercept value is negative.
B)slope value is negative.
C)slope value is zero.
D)Y-intercept value is zero.
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15
What is the slope of the following regression equation? <strong>What is the slope of the following regression equation?   = -8.27X + 3.09</strong> A)8.27 B)-8.27 C)3.09 D)-3.09 = -8.27X + 3.09

A)8.27
B)-8.27
C)3.09
D)-3.09
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16
The Y-intercept is the value of <strong>The Y-intercept is the value of   when X equals</strong> A)1.0 B)0.0 C)-1.0 D)2.0 when X equals

A)1.0
B)0.0
C)-1.0
D)2.0
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17
Which of the following is NOT representative of a strong relationship?

A)Y scores that are relatively close to their corresponding <strong>Which of the following is NOT representative of a strong relationship?</strong> 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   scores.
B)A correlation coefficient close to 1.
C)Y scores that are spread out.
D)Less prediction error and a smaller value of <strong>Which of the following is NOT representative of a strong relationship?</strong> 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
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18
Which of the following formulas represents the slope of the regression line?

A) <strong>Which of the following formulas represents the slope of the regression line?</strong> A)   B)   C)   D)
B) <strong>Which of the following formulas represents the slope of the regression line?</strong> A)   B)   C)   D)
C) <strong>Which of the following formulas represents the slope of the regression line?</strong> A)   B)   C)   D)
D) <strong>Which of the following formulas represents the slope of the regression line?</strong> A)   B)   C)   D)
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19
<strong>  is</strong> A)the actual Y scores. B)the predicted Y scores. C)the standard deviation of Y. D)the standard error of the estimate. is

A)the actual Y scores.
B)the predicted Y scores.
C)the standard deviation of Y.
D)the standard error of the estimate.
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20
If there is no relationship between two variables,the slope of the regression line will equal

A)1.0
B)0.5
C)0.0
D)-1.0
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21
For the following data,what is the predicted test score for a person with a stress level of 10? <strong>For the following data,what is the predicted test score for a person with a stress level of 10?  </strong> A)0.76 B)20.93 C)-7.16 D)12.43

A)0.76
B)20.93
C)-7.16
D)12.43
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22
One assumption of linear regression is

A)the Y scores at each X form an approximately normal distribution.
B)the X scores at each Y form an approximately normal distribution.
C)at each X,both the X and Y score samples should represent an approximately normal distribution.
D)at each X,approximately 68% of all Y scores should be between <strong>One assumption of linear regression is</strong> A)the Y scores at each X form an approximately normal distribution. B)the X scores at each Y form an approximately normal distribution. C)at each X,both the X and Y score samples should represent an approximately normal distribution. D)at each X,approximately 68% of all Y scores should be between   . .
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23
For the following data,what is the standard error of the estimate? <strong>For the following data,what is the standard error of the estimate?  </strong> A)3.71 B)5.72 C)32.72 D)1,070.49

A)3.71
B)5.72
C)32.72
D)1,070.49
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24
For the following data,what is the regression equation? <strong>For the following data,what is the regression equation?  </strong> A)   = 20.93X - 0.85 B)   = -0.85 X + 20.93 C)   = 20.93 X + 0.85 D)   = 0.85 X + 20.93

A) <strong>For the following data,what is the regression equation?  </strong> A)   = 20.93X - 0.85 B)   = -0.85 X + 20.93 C)   = 20.93 X + 0.85 D)   = 0.85 X + 20.93 = 20.93X - 0.85
B) <strong>For the following data,what is the regression equation?  </strong> A)   = 20.93X - 0.85 B)   = -0.85 X + 20.93 C)   = 20.93 X + 0.85 D)   = 0.85 X + 20.93 = -0.85 X + 20.93
C) <strong>For the following data,what is the regression equation?  </strong> A)   = 20.93X - 0.85 B)   = -0.85 X + 20.93 C)   = 20.93 X + 0.85 D)   = 0.85 X + 20.93 = 20.93 X + 0.85
D) <strong>For the following data,what is the regression equation?  </strong> A)   = 20.93X - 0.85 B)   = -0.85 X + 20.93 C)   = 20.93 X + 0.85 D)   = 0.85 X + 20.93 = 0.85 X + 20.93
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25
The sum of the deviations of the true Y scores from the predicted <strong>The sum of the deviations of the true Y scores from the predicted   scores is always</strong> A)zero. B)a very large number. C)equal to N times the mean of Y. D)negative. scores is always

A)zero.
B)a very large number.
C)equal to N times the mean of Y.
D)negative.
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26
Homoscedasticity occurs when

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 Y' scores are spread out to the same degree at every X.
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27
A nutrition major at State University was studying the relationship between carbohydrates (X)and calories (Y).For example,a serving of a particular brand of wheat pasta yielded 42 carbohydrates and 210 calories.After collecting X and Y data on many kinds of foods,the student determined the slope of the regression line to be 4.0 and the Y intercept to be 3.0.If a new food is tested,and the number of carbohydrates (X)is 100,what would be the predicted calories ( <strong>A nutrition major at State University was studying the relationship between carbohydrates (X)and calories (Y).For example,a serving of a particular brand of wheat pasta yielded 42 carbohydrates and 210 calories.After collecting X and Y data on many kinds of foods,the student determined the slope of the regression line to be 4.0 and the Y intercept to be 3.0.If a new food is tested,and the number of carbohydrates (X)is 100,what would be the predicted calories (   )?</strong> A)304 B)403 C)305 D)504 )?

A)304
B)403
C)305
D)504
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28
If the correlation coefficient turns out to be a relatively high value,then the value of <strong>If the correlation coefficient turns out to be a relatively high value,then the value of   will be</strong> A)relatively low. B)relatively high. C)unrelated to the value of r. D)low if r is positive and high if r is negative. will be

A)relatively low.
B)relatively high.
C)unrelated to the value of r.
D)low if r is positive and high if r is negative.
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29
The standard error of the estimate is similar to the

A)sum of the actual Y scores around their predicted Y' scores.
B)standard deviation of actual Y scores around their predicted Y' scores.
C)degree to which any predicted Y' will deviate from its actual Y score.
D)standard deviation of actual Y scores around their actual X scores.
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30
The "error" in a single prediction is equal to the degree to which a participant's ______ score deviates from the ______.

A)actual;mean
B)predicted;mean
C)predicted;given X
D)actual;corresponding predicted score
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31
In a study of the relationship between amount of sugar consumed (X)and excitability (Y)in children,the regression equation was calculated to be <strong>In a study of the relationship between amount of sugar consumed (X)and excitability (Y)in children,the regression equation was calculated to be   .The amount of sugar consumed ranged from 1 to 4 ounces.Which of the following graphs correctly displays the regression line?  </strong> A)Graph A B)Graph B C)Graph C D)Graph D .The amount of sugar consumed ranged from 1 to 4 ounces.Which of the following graphs correctly displays the regression line? <strong>In a study of the relationship between amount of sugar consumed (X)and excitability (Y)in children,the regression equation was calculated to be   .The amount of sugar consumed ranged from 1 to 4 ounces.Which of the following graphs correctly displays the regression line?  </strong> A)Graph A B)Graph B C)Graph C D)Graph D

A)Graph A
B)Graph B
C)Graph C
D)Graph D
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32
To predict a <strong>To predict a   score from a given X score using the regression equation,we would</strong> A)first multiply X by the slope and then add the Y-intercept. B)first multiply X by the Y-intercept and then add the slope. C)first add the Y-intercept to X and then multiply by the slope. D)first add the slope to X and then multiply by the Y-intercept. score from a given X score using the regression equation,we would

A)first multiply X by the slope and then add the Y-intercept.
B)first multiply X by the Y-intercept and then add the slope.
C)first add the Y-intercept to X and then multiply by the slope.
D)first add the slope to X and then multiply by the Y-intercept.
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33
When heteroscedasticity exists,the problem with r is that it

A)does not accurately describe the predicted Y values.
B)is very large.
C)does not accurately describe the strength of the relationship for all Xs.
D)will equal 0.
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34
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? <strong>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?  </strong> A)   = -3.08X + 1.64 B)   = 9.5 X + 12.5 C)   <sup> </sup> = 2.69 X - 0.49 D)   <sup> </sup> = 1.64 X - 3.08

A) <strong>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?  </strong> A)   = -3.08X + 1.64 B)   = 9.5 X + 12.5 C)   <sup> </sup> = 2.69 X - 0.49 D)   <sup> </sup> = 1.64 X - 3.08 = -3.08X + 1.64
B) <strong>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?  </strong> A)   = -3.08X + 1.64 B)   = 9.5 X + 12.5 C)   <sup> </sup> = 2.69 X - 0.49 D)   <sup> </sup> = 1.64 X - 3.08 = 9.5 X + 12.5
C) <strong>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?  </strong> A)   = -3.08X + 1.64 B)   = 9.5 X + 12.5 C)   <sup> </sup> = 2.69 X - 0.49 D)   <sup> </sup> = 1.64 X - 3.08 = 2.69 X - 0.49
D) <strong>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?  </strong> A)   = -3.08X + 1.64 B)   = 9.5 X + 12.5 C)   <sup> </sup> = 2.69 X - 0.49 D)   <sup> </sup> = 1.64 X - 3.08 = 1.64 X - 3.08
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35
Heteroscedasticity occurs when

A)there is a nonlinear relationship between the X and Y scores.
B)the <strong>Heteroscedasticity occurs when</strong> 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. 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.
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36
Computing the standard error of the estimate ( <strong>Computing the standard error of the estimate (   )by subtracting each   from the corresponding Y,squaring the difference,summing the results,dividing by N,and then taking the square root (the defining formula)is difficult and time-consuming.Fortunately,the same value can be computed by multiplying the standard deviation of Y (i.e. ,   )by</strong> A)100 B)   C)   D)0.5 )by subtracting each <strong>Computing the standard error of the estimate (   )by subtracting each   from the corresponding Y,squaring the difference,summing the results,dividing by N,and then taking the square root (the defining formula)is difficult and time-consuming.Fortunately,the same value can be computed by multiplying the standard deviation of Y (i.e. ,   )by</strong> A)100 B)   C)   D)0.5 from the corresponding Y,squaring the difference,summing the results,dividing by N,and then taking the square root (the defining formula)is difficult and time-consuming.Fortunately,the same value can be computed by multiplying the standard deviation of Y (i.e. , <strong>Computing the standard error of the estimate (   )by subtracting each   from the corresponding Y,squaring the difference,summing the results,dividing by N,and then taking the square root (the defining formula)is difficult and time-consuming.Fortunately,the same value can be computed by multiplying the standard deviation of Y (i.e. ,   )by</strong> A)100 B)   C)   D)0.5 )by

A)100
B) <strong>Computing the standard error of the estimate (   )by subtracting each   from the corresponding Y,squaring the difference,summing the results,dividing by N,and then taking the square root (the defining formula)is difficult and time-consuming.Fortunately,the same value can be computed by multiplying the standard deviation of Y (i.e. ,   )by</strong> A)100 B)   C)   D)0.5
C) <strong>Computing the standard error of the estimate (   )by subtracting each   from the corresponding Y,squaring the difference,summing the results,dividing by N,and then taking the square root (the defining formula)is difficult and time-consuming.Fortunately,the same value can be computed by multiplying the standard deviation of Y (i.e. ,   )by</strong> A)100 B)   C)   D)0.5
D)0.5
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37
When r = 1.0,then <strong>When r = 1.0,then   equals</strong> A)r B)0 C)1.0 D)   equals

A)r
B)0
C)1.0
D) <strong>When r = 1.0,then   equals</strong> A)r B)0 C)1.0 D)
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38
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 standard error of the estimate? <strong>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 standard error of the estimate?  </strong> A)2.31 B)4.86 C)5.34 D)1.52

A)2.31
B)4.86
C)5.34
D)1.52
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39
When there is no relationship between two variables,the value of every <strong>When there is no relationship between two variables,the value of every   is equal to</strong> A)the value of every X. B)the value of every Y. C)the value of the Y-intercept. D)zero. is equal to

A)the value of every X.
B)the value of every Y.
C)the value of the Y-intercept.
D)zero.
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40
When r = 0.0,the value of <strong>When r = 0.0,the value of   is equal to</strong> A)   B)0 C)1.0 D)   is equal to

A) <strong>When r = 0.0,the value of   is equal to</strong> A)   B)0 C)1.0 D)
B)0
C)1.0
D) <strong>When r = 0.0,the value of   is equal to</strong> A)   B)0 C)1.0 D)
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41
The coefficient of alienation is interpreted as the

A)amount of variance determined in all the Y scores.
B)alienation of variance in all the Y scores.
C)degree to which the scores are efficient.
D)proportion of variance not accounted for.
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42
When we square the correlation coefficient to produce <strong>When we square the correlation coefficient to produce   ,the result is equal to the</strong> A)proportion of variance not accounted for. B)proportion of variance accounted for. C)standard error of the estimate. D)coefficient of alienation. ,the result is equal to the

A)proportion of variance not accounted for.
B)proportion of variance accounted for.
C)standard error of the estimate.
D)coefficient of alienation.
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43
We calculate the proportion of variance accounted for because it is the statistical basis for evaluating

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.
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44
The coefficient of determination is interpreted as the

A)amount of variance determined in all the Y scores.
B)determined amount of variance in all the Y scores.
C)degree to which the scores are efficient.
D)proportion of variance accounted for.
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45
For the following data,what is the proportion of variance accounted for? <strong>For the following data,what is the proportion of variance accounted for?  </strong> A)-0.76 B)0.58 C)0.76 D)-0.58

A)-0.76
B)0.58
C)0.76
D)-0.58
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46
When we use a relationship to predict scores,our error is

A)the mean of Y.
B)the mean of X.
C) <strong>When we use a relationship to predict scores,our error is</strong> A)the mean of Y. B)the mean of X. C)   . D)   . .
D) <strong>When we use a relationship to predict scores,our error is</strong> A)the mean of Y. B)the mean of X. C)   . D)   . .
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47
In general,the greater the proportion of variance accounted for,

A)the more error there is in the data.
B)the less accurately we can predict behavior.
C)the more accurately we can predict behavior.
D)the less important the relationship to our ability to make predictions.
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48
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?

A)0.73
B)0.47
C)0.28
D)0.53
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49
Compared to a strong relationship,a weak relationship between two variables results in

A)greater prediction error and a larger value of <strong>Compared to a strong relationship,a weak relationship between two variables results in</strong> A)greater prediction error and a larger value of   . B)greater prediction error and a smaller value of   . C)less prediction error and a larger value of   . D)less<sub> </sub>prediction error and a smaller value of   . .
B)greater prediction error and a smaller value of <strong>Compared to a strong relationship,a weak relationship between two variables results in</strong> A)greater prediction error and a larger value of   . B)greater prediction error and a smaller value of   . C)less prediction error and a larger value of   . D)less<sub> </sub>prediction error and a smaller value of   . .
C)less prediction error and a larger value of <strong>Compared to a strong relationship,a weak relationship between two variables results in</strong> A)greater prediction error and a larger value of   . B)greater prediction error and a smaller value of   . C)less prediction error and a larger value of   . D)less<sub> </sub>prediction error and a smaller value of   . .
D)less prediction error and a smaller value of <strong>Compared to a strong relationship,a weak relationship between two variables results in</strong> A)greater prediction error and a larger value of   . B)greater prediction error and a smaller value of   . C)less prediction error and a larger value of   . D)less<sub> </sub>prediction error and a smaller value of   . .
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50
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? <strong>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?  </strong> A)0.77 B)2.31 C)0.23 D)4.86

A)0.77
B)2.31
C)0.23
D)4.86
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51
The coefficient of determination is equal to

A) <strong>The coefficient of determination is equal to</strong> A)   . B)   . C)   . D)   .
B) <strong>The coefficient of determination is equal to</strong> A)   . B)   . C)   . D)   .
C) <strong>The coefficient of determination is equal to</strong> A)   . B)   . C)   . D)   .
D) <strong>The coefficient of determination is equal to</strong> A)   . B)   . C)   . D)
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52
When we divide the error remaining after we use the relationship to predict Y scores ( <strong>When we divide the error remaining after we use the relationship to predict Y scores (   )by the total error when we use the mean to predict the Y scores (   )and then subtract the result from 1,the final result is the</strong> A)proportion of variance not accounted for. B)proportion of variance accounted for. C)standard error of the estimate. D)coefficient of alienation. )by the total error when we use the mean to predict the Y scores ( <strong>When we divide the error remaining after we use the relationship to predict Y scores (   )by the total error when we use the mean to predict the Y scores (   )and then subtract the result from 1,the final result is the</strong> A)proportion of variance not accounted for. B)proportion of variance accounted for. C)standard error of the estimate. D)coefficient of alienation. )and then subtract the result from 1,the final result is the

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