Deck 12: Prediction

Question 1

A person's predicted score on the criterion variable is found by multiplying the person's score on the predictor variable by a particular number called a

A)coefficient of redundancy.
B)regression constant.
C)proportionate reduction in error.
D)regression coefficient.

Answer 1

regression coefficient.

Question 2

When a person's score on one variable is used to make predictions about a person's score on another variable,the procedure is called

A)a correlation.
B)hypothesis testing.
C)bivariate prediction.
D)multicollinearity.

Answer 2

bivariate prediction.

Question 3

A regression line

A)is drawn on a graph in which scores for the predicted variable are on the horizontal axis.
B)is rarely a straight line.
C)can be shown on a bar graph.
D)shows the relation between values of the predictor and criterion variables.

Answer 3

shows the relation between values of the predictor and criterion variables.

Question 4

If a person's score on a questionnaire has been found to predict observed social skills,and the linear prediction rule uses a regression constant of 16 and a regression coefficient of 3,the predicted level of social skills for a person with a score of 10 on the questionnaire is

A)10
B)46
C)160
D)190

Question 5

If a child psychologist reports that age in months predicts appetite level for a group of infants using a linear prediction rule in which a = 1 and b = 2,the appetite level for a four-month-old infant is

A)4
B)8
C)9
D)12

Question 6

Error in regression is figured by

A)Y - X .
B)Y - Ŷ .
C)Y - b .
D)Y - a .

Question 7

The regression coefficient in the best linear prediction rule is

A)the product of the sum of the deviation scores on the predictor variable,multiplied by the sum of the deviation scores on the criterion variable,divided by the predictor variable's sum of squared deviations from the mean.
B)the sum of the products of the deviation scores,divided by the predictor variable's sum of squared deviations from the mean.
C)the product of the sum of the deviation scores on the predictor variable,multiplied by the sum of the deviation scores on the criterion variable,divided by the criterion variable's sum of squared deviations from the mean.
D)the sum of the product of the deviation scores,divided by the criterion variable's sum of squared deviations from the mean.

Question 8

If a counseling psychologist wants to predict college grades from high school grades,college grades are the

A)predictor variable.
B)criterion variable.
C)independent variable.
D)causal variable.

Question 9

On a scatter diagram,the vertical distance between the dot for the actual score and the regression line represents the

A)slope.
B)regression constant.
C)squared error.
D)error.

Question 10

When drawing a regression line for a linear prediction rule,the minimum number of predicted points on a graph that must be located is

A)1.
B)2.
C)1 if it is a positively sloped line; 2 if it is a negatively sloped line.
D)2 if it is a positively sloped line; 1 if it is a negatively sloped line.

Question 11

Why are errors squared in a regression?

A)to give more weight to smaller errors
B)because summing positive and negative errors will cancel them out
C)multiplying positive and negative errors will always result in negative numbers
D)errors are not actually squared in a regression

Question 12

If every increase of one point on a test-anxiety scale is associated with a decrease of 2 points on predicted performance on a test,2 represents the slope,which is also the

A)regression coefficient.
B)regression constant.
C)proportionate reduction in error.
D)standardized regression coefficient.

Question 13

The term in a linear prediction rule that represents the intercept of a regression line is

A)a.
B)b.
C)X.
D)Ŷ.

Question 14

The sum of squared errors is the sum of

A)each score on the criterion variable minus the predicted score,squared.
B)each squared score on the criterion variable minus each squared predicted score.
C)each score on the predictor variable minus the predicted score,squared.
D)each squared score on the predictor variable minus each squared predicted score.

Question 15

A regression coefficient indicates

A)whether the correlation is significant or not.
B)how many units of change in the predicted value of the criterion variable for each unit of change in the predictor variable.
C)the accuracy of predictions based on the reduction in squared error as a proportion of the total squared error.
D)the fixed amount that should be added when making a prediction for any particular person.

Question 16

The regression constant is also referred to as

A)error.
B)a slope.
C)the X intercept.
D)the Y intercept.

Question 17

The best linear prediction rule is the one that has the least

A)error when predicting from the mean.
B)squared error when predicting from the mean.
C)error when predicting using that rule.
D)squared error when predicting using that rule.

Question 18

Considering the number of possible linear prediction rules for predicting Y from X,for any particular set of scores,

A)all rules are equally valid,and it does not matter which one is used.
B)there is one best rule for positive predictions and one best rule for negative predictions.
C)there is one best rule for predicting low scores and one best rule for predicting high scores.
D)there is only one best rule.

Question 19

In the equation Ŷ = a + (b)(X),b is the symbol for the

A)correlation coefficient.
B)regression coefficient.
C)proportionate reduction in error.
D)regression constant.

Question 20

When making predictions using a linear prediction rule,the baseline number that is added to each prediction is

A)a.
B)b.
C)X.
D)Ŷ.

Question 21

The regression constant in the best linear prediction rule is

A)the mean of the criterion variable minus the result of multiplying the regression coefficient by the mean of the predictor variable.
B)the mean of the criterion variable plus the result of multiplying the regression coefficient by the mean of the predictor variable.
C)the mean of the criterion variable minus the result of dividing the regression coefficient by the mean of the predictor variable.
D)the mean of the criterion variable plus the result of dividing the regression coefficient by the mean of the predictor variable.

Question 22

Advanced topic: What is the formula for the proportionate reduction in error?

A)(SS_Error - SS_Total)/ SS_Error
B)(SS_Error + SS_Total)/ SS_Error
C)(SS_Total - SS_Error)/ SS_Total
D)SS_Total / (SS_Error + SS_Total)

Question 23

In a bivariate linear prediction,the null hypothesis is that

A)β = 0 .
B)β = 1 .
C)β ≠ 0 .
D)β ≠ 1 .

Question 24

The multiple correlation coefficient of a criterion variable with two predictor variables

A)is usually smaller than the sum of the correlation coefficients of the criterion variable with each predictor variable.
B)is usually larger than the sum of the correlation coefficients of the criterion variable with each predictor variable.
C)is exactly the same as the sum of the correlation coefficients of the criterion variable with each predictor variable.
D)can be larger,smaller,or the same as the sum of the correlation coefficients of the criterion variable with each predictor variable.

Question 25

When multiple regression statistics are reported in a psychology research article,

A)the correlation coefficients for the predictor variables usually appear in the text.
B)the unstandardized regression coefficients for the predictor variables usually appear in the text.
C)the standardized regression coefficients for the predictor variables usually appear in the text.
D)the coefficients for the predictor variables (be it b,β,or both)usually appear in a table.

Question 26

In psychology research articles,

A)linear prediction rules are usually presented for bivariate but not multiple regression.
B)when results for bivariate prediction are reported,it is most likely to be with regression lines.
C)if multiple regression results are reported,the bivariate correlations will usually not be reported.
D)if a standardized regression coefficient (β)is reported,the bivariate correlation (r)will almost always be reported as well.

Question 27

An educational psychologist wants to predict how well students will do on a particular multiple-choice test based on a measure of their ability to follow instructions. Their actual scores are 3, 7, and 11, and their respective predicted scores are 5, 7, and 9.
Advanced topic: What is SS_Total?

A)(3-7)² + (7-7)² + (11-7)²
B)(5-7)² + (7-7)² + (9-7)²
C)(3-5)² + (7-7)² + (11-9)²
D)(5-9)² + (7-9)² + (9-9)²

Question 28

Which limitation is applicable to both correlation and regression?

A)The degree of predictability will be underestimated if the underlying relationship is linear.
B)Nothing can be inferred about the direction of causality.
C)Restrictions in range and unreliable measures are uncommon.
D)The relative importance of different predictor variables cannot be assessed.

Question 29

Advanced topic: What does it mean when SS_Total minus SS_Error equals zero?

A)This is the best case-it means there is zero error.
B)This is the worst case-it means the prediction model has reduced zero error.
C)The proportionate reduction in error is 50%.
D)The underlying correlation is negative.

Question 30

Advanced topic: What is the difference between the SS_Error and SS_Total?

A)SS_Error is an individual score; SS_Total takes into account the error of an entire study.
B)SS_Error uses the prediction rule; SS_Total predicts from the mean.
C)SS_Error predicts from the mean; SS_Total uses the prediction rule.
D)SS_Error takes into account the variance of both populations; SS_Total takes into account only the variance in the predictor variable.

Question 31

The statistical procedure used to make predictions about people's poetic ability based on their scores on a general writing ability test and their scores on a creativity test is

A)ridge regression.
B)multiple regression.
C)bivariate regression.
D)proportion of variance accounted for.

Question 32

In a linear prediction rule using a standardized regression coefficient,

A)the regression constant is always equal to 1.
B)for each increase of one standard deviation in the predictor variable,the predicted standard deviation of the criterion variable increases by the standardized regression coefficient.
C)the predicted value for the criterion variable is a t score.
D)for each increase of one standard deviation in the predicted variable,the predicted standard deviation of the predictor variable increases by the standardized regression coefficient.

Question 33

An educational psychologist wants to predict how well students will do on a particular multiple-choice test based on a measure of their ability to follow instructions. Their actual scores are 3, 7, and 11, and their respective predicted scores are 5, 7, and 9.
Advanced topic: What is SS_Error?

A)(3-7)² + (7-7)² + (11-7)²
B)(5-7)² + (7-7)² + (9-7)²
C)(3-5)² + (7-7)² + (11-9)²
D)(5-9)² + (7-9)² + (9-9)²

Question 34

Advanced topic: If the correlation coefficient for a study is known,figuring the proportionate reduction in error requires

A)dividing the correlation coefficient by 2.
B)taking the square root of the correlation coefficient.
C)squaring the correlation coefficient.
D)multiplying the correlation coefficient by 2.

Question 35

Which assumption is applicable to regression but not to correlation?

A)linear relationship between the variables
B)independence of people (or cases)
C)error scores are normally distributed
D)each variable is equally distributed at each point of the other variable

Question 36

The multiple regression formula with two predictor variables is

A)Ŷ = a + (b₁/X₁)+ (b₂/X₂).
B)Ŷ = a₁ + a₂ + (b₁/X1)+ (b₂/X₂).
C)Ŷ = a + (b₁)(X₁)+ (b₂)(X₂).
D)Ŷ = a₁ + a₂ + (b₁)(X₁)+ (b₂)(X₂).

Question 37

An educational psychologist wants to predict how well students will do on a particular multiple-choice test based on a measure of their ability to follow instructions. Their actual scores are 3, 7, and 11, and their respective predicted scores are 5, 7, and 9.
Advanced topic: What is the proportionate reduction in error?

A)(32 - 8)/ 32 = 0.75
B)(8 - 32)/ 8 = -3
C)32 / (8 + 32)= 0.80
D)(8 + 32)/ 8 = 5

Question 38

Which of the following is true about hypothesis testing for a linear prediction rule?

A)If the correlation coefficient is significant,the regression coefficient will be significant.
B)If the correlation coefficient is significant,the standardized regression coefficient will be significant,but the unstandardized (ordinary)regression coefficient will not.
C)The t test for the correlation coefficient tests the significance of the regression constant.
D)The t test for the correlation coefficient tests the significance of both the regression constant and the regression coefficient.

Question 39

The standardized regression coefficient in a bivariate linear prediction rule equals

A)the intercept of the regression line using raw scores.
B)the slope of the regression line using raw scores.
C)the correlation coefficient.
D)the correlation coefficient squared.

Question 40

Advanced topic: The sum of the squared errors when predicting from the mean is called

A)SS_Error.
B)proportionate reduction in error.
C)SS_Total.
D)proportion of variance accounted for.

Question 41

If the predicted score for a person with a predictor variable score of 1 is 19.5 and for a person with a predictor variable score of 2 is 21.5,the regression coefficient is __________.(Give a number.)

Question 42

In making a prediction using the linear prediction rule,Ŷ = 7 + (1.28)(X),the "7" is the __________.(Give a name,not a symbol.)

Question 43

based on the following data for variables X and Y.
The regression coefficient for the best linear prediction rule is __________.(Give a number.)

Question 44

The regression coefficient is the number multiplied by the score on the predictor variable to get the __________ on the criterion variable.(Give a name,not a symbol.)

Question 45

The slope of the regression line corresponds to the __________.(Give a name,not a symbol.)

Question 46

The number multiplied by the score on the predictor variable to get the predicted score on the criterion variable is the __________.(Give a name,not a symbol.)

Question 47

In prediction,error is the person's actual score minus the person's __________.(Give a name,not a symbol.)

Question 48

If Ŷ = 3 + (.25)(X),a person whose score on X is 100 and on Y is 22 has a squared error of __________.(Give a number.)

Question 49

In making a prediction using the linear prediction rule,Ŷ = 7 + (1.28)(X),the "1.28" is the __________.(Give a name,not a symbol.)

Question 50

based on the following data for variables X and Y.
To find the standardized regression coefficient for the best linear prediction rule,divide the square root of __________ by the square root of __________,and multiply the result by the unstandardized (ordinary)regression coefficient.(Give numbers.)

Question 51

If a cognitive psychologist is studying whether difficulty doing a task predicts the amount of activity in a certain brain area,task difficulty is the __________ variable,and brain activity is the __________ variable.(Give names,not symbols.)

Question 52

based on the following data for variables X and Y.
The regression constant for the best linear prediction rule is __________.(Give a number.)

Question 53

based on the following data for variables X and Y.
The standardized regression coefficient for the best linear prediction rule is __________.(Give a number.)

Question 54

Prediction is also called __________.

Question 55

If a regression line goes up three units for every one unit it moves across going from left to right,b = __________.(Give a number.)

Question 56

based on the following data for variables X and Y.
To find the regression coefficient for the best linear prediction rule,divide __________ by __________.(Give numbers.)

Question 57

The best linear prediction rule will have the smallest sum of __________.(Give a name,not a symbol.)

Question 58

The principle for selecting the best linear prediction rule is called the __________ criterion.

Question 59

One assumption of multiple regression is that error scores are __________.

Question 60

based on the following data for variables X and Y.
To find the regression constant for the best linear prediction rule,take __________ minus the result of multiplying the regression coefficient by __________.(Give numbers.)

Question 61

Advanced topic: The proportionate reduction in error is the sum of squared error when predicting from the mean minus the sum of squared error when predicting using the __________.

Question 62

A social psychologist conducted a study of whether similarity to a potential date (X)predicted attraction to that potential date (Y).The results for four participants follow. a.Figure the linear prediction rule.
b.Make a graph with the regression line.
c.Figure the standardized regression coefficient.
d.Explain the logic of what you did to someone who is familiar with correlation,but who knows nothing about prediction.Be sure your answer explains the ideas of prediction,linear prediction rule,best linear prediction rule,the regression line,and the standardized regression coefficient.
e.Advanced topic: Figure the proportionate reduction in error using sums of squared errors.
f.Advanced topic: Explain the logic behind how you figured the proportionate reduction in error.

Question 63

A psychologist conducted a study of burnout among social workers working with homeless people in a particular city.The study produced the following multiple regression prediction rule.Burnout was measured by a standard scale with 0 = low burnout and 48 = high burnout.The predictor variables,except months working at this job,were measured on a 4-point scale,with 1 = low and 4 = high. a.Figure the predicted burnout for a social worker who rates her sense of success on the job as a 4,her relationship with her supervisor as a 3,and who has been working at the job for 10 months.
b.Figure the predicted burnout for a social worker who rates his sense of success on the job as a 1,his relationship with his supervisor as a 1,and who has been working at the job for 20 months.
c.Figure the predicted burnout for a social worker who rates her sense of success on the job as a 3,her relationship with her supervisor as a 3,and who has been working at the job for 20 months.
d.Explain the logic of what you did,including why the predictions for the three people are different,to a person who is familiar with correlation,but who knows nothing about regression.

Question 64

A health psychologist conducts a study on whether the percentage of fat in a person's diet (X)predicts the percentage of time the person uses a seat belt (Y),with the idea that those who practice one kind of health-related behavior may be more likely to practice another.The results were: a.Figure the linear prediction rule.
b.Make a graph with the regression line.
c.Figure the standardized regression coefficient.
d.Explain the logic of what you did to someone who is familiar with correlation,but who knows nothing about prediction.Be sure your answer explains the ideas of prediction,linear prediction rule,best linear prediction rule,the regression line,and the standardized regression coefficient.
e.Advanced topic: Figure the proportionate reduction in error using sums of squared errors.
f.Advanced topic: Explain the logic behind how you figured the proportionate reduction in error.

Question 65

In a multiple regression situation with two predictors,the correlation of the first predictor with the criterion is .13; the correlation of the second predictor variable with the criterion is .12.Because the two predictor variables are correlated with each other,the multiple correlation coefficient will be __________ .25.

Question 66

A psychologist surveys a group of working married women to see if contribution to income (X)predicts contribution to housework (Y).(Contributions are proportions,but they have been converted to whole numbers to make figuring easier.)The results for four women follow: a.Figure the linear prediction rule.
b.Make a graph with the regression line.
c.Figure the standardized regression coefficient.
d.Explain the logic of what you did to someone who is familiar with correlation,but who knows nothing about prediction.Be sure your answer explains the ideas of prediction,linear prediction rule,best linear prediction rule,the regression line,and the standardized regression coefficient.
e.Advanced topic: Figure the proportionate reduction in error using sums of squared errors.
f.Advanced topic: Explain the logic behind how you figured the proportionate reduction in error.

Question 67

In a multiple regression situation with two predictors,β __________ r.(Write words,no symbols.)

Question 68

A social psychologist examining whether length of court trials (X)predicts length of time for juries to come to a decision (Y),reports the following results for the first four trials studied. a.Figure the linear prediction rule.
b.Make a graph with the regression line.
c.Figure the standardized regression coefficient.
d.Explain the logic of what you did to someone who is familiar with correlation,but who knows nothing about prediction.Be sure your answer explains the ideas of prediction,linear prediction rule,best linear prediction rule,the regression line,and the standardized regression coefficient.
e.Advanced topic: Figure the proportionate reduction in error using sums of squared errors.
f.Advanced topic: Explain the logic behind how you figured the proportionate reduction in error.

Question 69

A cognitive psychologist conducted a study of whether familiarity of words (X)predicts the time it takes (in seconds)to press a button indicating whether the word is singular or plural (Y),with all participants being given the same words.Familiarity with these words was rated at a later time on a 7-point scale (with higher numbers indicating more familiarity).The participants' scores were: a.Figure the linear prediction rule.
b.Make a graph with the regression line.
c.Figure the standardized regression coefficient.
d.Explain the logic of what you did to someone who is familiar with correlation,but who knows nothing about prediction.Be sure your answer explains the ideas of prediction,linear prediction rule,best linear prediction rule,the regression line,and the standardized regression coefficient.
e.Advanced topic: Figure the proportionate reduction in error using sums of squared errors.
f.Advanced topic: Explain the logic behind how you figured the proportionate reduction in error.

Question 70

Advanced topic: When figuring r2,you divide the reduction in squared error by the __________.(Do not give a symbol.)

Question 71

Researchers recommend comparing __________ to __________ when determining a predictor's relative importance.(Give symbols.)

Question 72

A health psychologist surveyed 200 female outpatients at a health maintenance organization and figured a multiple regression prediction rule for predicting compliance (the degree to which patients follow the prescribed medication orders)on a scale from 0 = not at all to 100 = completely.The predictor variables were all rated on 7-point scales with 1 = low and 7 = high.
Predicted compliance = 60 + (4)(trust in own doctor)
+ (10)(trust in doctors generally)
- (5)(past bad experiences with medications)

A)Figure the predicted compliance for a woman who rated her trust in her own doctor as a 3,her trust in doctors generally as a 3,and her past bad experience with medications as a 7.
B)Figure the predicted compliance for a woman who rated her trust in her own doctor as a 3,her trust in doctors generally as a 3,and her past bad experience with medications as a 1.
C)Figure the predicted compliance for a woman who rated her trust in her own doctor as a 3,her trust in doctors generally as a 1,and her past bad experience with medications as a 1.
D)Explain the logic of what you did,including why the predictions for the three women are different,to a person who is familiar with correlation,but who knows nothing about regression.

Question 73

A researcher was interested in whether college GPA (X)would predict starting salary after college (Y).(For simplicity,salary was converted to a 100-point scale.)The participants' scores were: a.Figure the linear prediction rule.
b.Make a graph with the regression line.
c.Figure the standardized regression coefficient.
d.Explain the logic of what you did to someone who is familiar with correlation,but who knows nothing about prediction.Be sure your answer explains the ideas of prediction,linear prediction rule,best linear prediction rule,the regression line,and the standardized regression coefficient.
e.Advanced topic: Figure the proportionate reduction in error using sums of squared errors.
f.Advanced topic: Explain the logic behind how you figured the proportionate reduction in error.