Question 1

When the correlation is perfect, every value of ____________ is zero.

Accepted Answer

A)    
B)    
C)    
D)  all of the above 
A)    
B)    
C)    
D)  all of the above A

Question 2

and   
;   
 and   
 If   
 and X is 40, what value do we predict for Y?

Accepted Answer

A)  120 
B)  100 
C)  80 
D)  0 
A)  120 
B)  100 
C)  80 
D)  0 B

Question 3

and   
;   
 and   
 If   
 and X is 40, what value do we predict for Y?

Accepted Answer

A)  120 
B)  100 
C)  90 
D)  80 
A)  120 
B)  100 
C)  90 
D)  80 A

Question 4

A formula for the standard error of estimate of Y on X is

Accepted Answer

A)    
B)    
C)    
D)  none of the above 
A)    
B)    
C)    
D)  none of the above

Question 5

For the group of adult joggers competing in the Windy City Mini-marathon, the following are the summary statistics for annual income (X) and time to complete the race (Y):
   (a)  Jack L. and Linda P. have annual incomes of $12,372 and $24,812, respectively. What race times would you predict? (Hint: No calculations are necessary). (b) What general principle is illustrated by this problem?

Accepted Answer

(a) 122.38 minutes f

Question 6

The standard error of estimate is a kind of

Accepted Answer

A)  mean 
B)  median 
C)  standard deviation 
D)  variance 
A)  mean 
B)  median 
C)  standard deviation 
D)  variance

Question 7

and   
;   
 and   
 If   
 and X is 40, what value do we predict for Y?

Accepted Answer

A)  120 
B)  100 
C)  90 
D)  80 
A)  120 
B)  100 
C)  90 
D)  80

Question 8

The raw score regression equation always

Accepted Answer

A)  intersects the origin of the graph (the point where   
 and 
   
B)  intersects the point where   
 and 
   
C)  slopes from lower left to upper right 
D)  slopes from upper left to lower right 
A)  intersects the origin of the graph (the point where   
 and 
   
B)  intersects the point where   
 and 
   
C)  slopes from lower left to upper right 
D)  slopes from upper left to lower right

Question 9

In predicting Y from X, the regression line is laid down so that the squared discrepancies between points and the line are minimized

Accepted Answer

A)  in the X dimension 
B)  in the Y dimension 
C)  in a direction perpendicular to the line 
D)  in all of the above dimensions 
A)  in the X dimension 
B)  in the Y dimension 
C)  in a direction perpendicular to the line 
D)  in all of the above dimensions

Question 10

John Jones falls one standard deviation above the mean of X.
(a)If his predicted score on Y falls one standard deviation above   what is the correlation between X and Y?
(b)If his predicted score on Y falls one-third of a standard deviation above    what is the correlation between X and Y?

Accepted Answer

The answer of John Jones falls one standard deviation above...

Question 11

The following are the scores on a job selection test administered prior to hiring (X) and supervisor's ratings after 3 months on the job (Y) for a group of bank tellers (A-F): 
   
(a) Compute from these data the summary statistics required for developing the raw-score regression equation for predicting supervisor's rating from job selection score.
(b) Use the values from (a) to arrive at the regression equation in simplest form. 
(c) Three new applicants for teller positions obtain scores of 48, 62, and 72, respectively, on the selection test. Compute their predicted supervisor's ratings. 
(d) If in fact the above data were real, what objection would you have to using the equation from (b) to predict in a "real-life" situation?

Accepted Answer

(a) @#IMG-DLM& (b) @#IMG-DLM&  
 
(c)7.3, 8.9, 10.1 (answers

Question 12

In concept, the regression line is most closely related to the

Accepted Answer

A)  mean 
B)  median 
C)  standard deviation 
D)  variance 
A)  mean 
B)  median 
C)  standard deviation 
D)  variance

Question 13

Which value of r permits the greatest accuracy of prediction?

Accepted Answer

A)  +.78 
B)  +.27 
C)  -.37 
D) -.81 
A)  +.78 
B)  +.27 
C)  -.37 
D) -.81

Question 14

The standard error of estimate measures variability of

Accepted Answer

A)  predicted scores around the mean 
B)  predicted scores around the regression line 
C)  obtained scores around the mean 
D)  obtained scores around the regression line 
A)  predicted scores around the mean 
B)  predicted scores around the regression line 
C)  obtained scores around the mean 
D)  obtained scores around the regression line

Question 15

From the records of a large health maintenance organization, an investigator is able to gather a sizeable sample of men for whom heights at both age 10 and as adults are known. The following are the summary statistics for this sample:
   
(a) Use the above values to arrive at the raw-score regression equation for predicting height as an adult from height at age 10. Present the equation in simplest form. 
(b) Use the regression equation from (a) to predict adult height for the following 10-year-olds: Benny (42.5 in.), Cal (55.3 in.), Arthur (50.1 in.). 
(c) Consider Benny's predictable adult height. In what sense is that value a mean? Be very specific.

Accepted Answer

(a) .94X + 21.9
(b) Benny: 61.

Question 16

For a large group of subjects:   
 and   
 Captain Crunch obtains an X score of 52. What is his predicted Y score if (no calculations necessary):
(a)   
(b)   
(c)   
(d)   
 (e)State the principal illustrated by your answers to (a) through (d).

Accepted Answer

(a)-(d)147.3

(e)if you are on

Question 17

What value of r leads us to predict that   no matter what the value of X?

Accepted Answer

A)  0 
B)  -1.00 
C)  +1.00 
D)  none of the above 
A)  0 
B)  -1.00 
C)  +1.00 
D)  none of the above

Question 18

Accuracy of prediction by the regression equation is enhanced by

Accepted Answer

A)  large samples 
B)  a linear relationship 
C)  both of the above 
D)  none of the above 
A)  large samples 
B)  a linear relationship 
C)  both of the above 
D)  none of the above

Question 19

When homoscedasticity holds, then

Accepted Answer

A)  Y variability is the same for all values of X 
B)    
C)  Y variability is the same for X variability 
D)  both X and Y are expressed in standard score form 
A)  Y variability is the same for all values of X 
B)    
C)  Y variability is the same for X variability 
D)  both X and Y are expressed in standard score form

Question 20

A standard score regression equation reads:   If the correlation coefficient is +.5 and Johnny is two standard deviations above the mean in X, what standard score position shall we predict for him in Y?

Accepted Answer

A)  +2.0 
B)  +1.5 
C)  +1.0 
D)  none of the above 
A)  +2.0 
B)  +1.5 
C)  +1.0 
D)  none of the above

When the correlation is perfect, every value of ____________ is zero.

and ; and If and X is 40, what value do we predict for Y?

and ; and If and X is 40, what value do we predict for Y?

A formula for the standard error of estimate of Y on X is

The standard error of estimate is a kind of

and ; and If and X is 40, what value do we predict for Y?

The raw score regression equation always

In predicting Y from X, the regression line is laid down so that the squared discrepancies between points and the line are minimized

John Jones falls one standard deviation above the mean of X. (a)If his predicted score on Y falls one standard deviation above what is the correlation between X and Y? (b)If his predicted score on Y falls one-third of a standard deviation above what is the correlation between X and Y?

In concept, the regression line is most closely related to the

Which value of r permits the greatest accuracy of prediction?

The standard error of estimate measures variability of

For a large group of subjects: and Captain Crunch obtains an X score of 52. What is his predicted Y score if (no calculations necessary): (a) (b) (c) (d) (e)State the principal illustrated by your answers to (a) through (d).

What value of r leads us to predict that no matter what the value of X?

Accuracy of prediction by the regression equation is enhanced by

When homoscedasticity holds, then

A standard score regression equation reads: If the correlation coefficient is +.5 and Johnny is two standard deviations above the mean in X, what standard score position shall we predict for him in Y?

Introduction

Frequency Distributions, Percentiles,

Graphic Representation of Frequency Distributions

Central Tendency

Variability and Standard Z Scores

Standard Scores and the Normal Curve

Correlation

Interpretive Aspects of Correlation and Regression

Probability

Random Sampling and Sampling Distributions

Introduction to Statistical Inference: Testing Hypotheses About Single Means Z and T

Interpreting the Results of Hypothesis Testing: Effect Size, Type I and Type II Errors, and Power

Testing Hypotheses About the Difference Between Two Independent Groups

Testing for a Difference

Inference About Correlation Coefficients

An Alternative to Hypothesis Testing: Confidence Intervals

Testing for Differences Among Three or More Groups: One-Way Analysis of Variance and Some Alternatives

Factorial Analysis of Variance

Chi-Square and Inference About Frequencies

Some Almost Assumption-Free Tests

Filters

Exam 8: Prediction

When the correlation is perfect, every value of ____________ is zero.

and ; and If and X is 40, what value do we predict for Y?

and ; and If and X is 40, what value do we predict for Y?

A formula for the standard error of estimate of Y on X is

The standard error of estimate is a kind of

and ; and If and X is 40, what value do we predict for Y?

The raw score regression equation always

In predicting Y from X, the regression line is laid down so that the squared discrepancies between points and the line are minimized

John Jones falls one standard deviation above the mean of X. (a)If his predicted score on Y falls one standard deviation above what is the correlation between X and Y? (b)If his predicted score on Y falls one-third of a standard deviation above what is the correlation between X and Y?

In concept, the regression line is most closely related to the

Which value of r permits the greatest accuracy of prediction?

The standard error of estimate measures variability of

For a large group of subjects: and Captain Crunch obtains an X score of 52. What is his predicted Y score if (no calculations necessary): (a) (b) (c) (d) (e)State the principal illustrated by your answers to (a) through (d).

What value of r leads us to predict that no matter what the value of X?

Accuracy of prediction by the regression equation is enhanced by

When homoscedasticity holds, then

A standard score regression equation reads: If the correlation coefficient is +.5 and Johnny is two standard deviations above the mean in X, what standard score position shall we predict for him in Y?

Introduction

Frequency Distributions, Percentiles,

Graphic Representation of Frequency Distributions

Central Tendency

Variability and Standard Z Scores

Standard Scores and the Normal Curve

Correlation

Interpretive Aspects of Correlation and Regression

Probability

Random Sampling and Sampling Distributions

Introduction to Statistical Inference: Testing Hypotheses About Single Means Z and T

Interpreting the Results of Hypothesis Testing: Effect Size, Type I and Type II Errors, and Power

Testing Hypotheses About the Difference Between Two Independent Groups

Testing for a Difference

Inference About Correlation Coefficients

An Alternative to Hypothesis Testing: Confidence Intervals

Testing for Differences Among Three or More Groups: One-Way Analysis of Variance and Some Alternatives

Factorial Analysis of Variance

Chi-Square and Inference About Frequencies

Some Almost Assumption-Free Tests

Filters