Question 1

The reason that regression on the mean does not result in all individuals being of average stature after several generations is that

Accepted Answer

A)  regression is not operative in problems in inheritance 
B)  negative regression is accompanied by positive regression 
C)  regression is accompanied by variability 
D)  regression applies only to the first generation 
A)  regression is not operative in problems in inheritance 
B)  negative regression is accompanied by positive regression 
C)  regression is accompanied by variability 
D)  regression applies only to the first generation C

Question 2

measures variation of

Accepted Answer

A)  obtained scores about the predicted scores 
B)  obtained scores about the mean 
C)  predicted scores about the obtained scores 
D)  predicted scores about the mean 
A)  obtained scores about the predicted scores 
B)  obtained scores about the mean 
C)  predicted scores about the obtained scores 
D)  predicted scores about the mean D

Question 3

If a regression equation reads:   we know that

Accepted Answer

A)    is greater than   
B)  SY is greater than SX 
C)  the correlation is negative 
D)  a mistake has been made in calculating r 
A)    is greater than   
B)  SY is greater than SX 
C)  the correlation is negative 
D)  a mistake has been made in calculating r B

Question 4

In one study, a correlation of +.45 was found between physical strength and ratings of popularity for a group of adolescent boys. What can be said about the degree to which differences in popularity can be "explained" by strength? Give your answer in terms of a percent. Percent of what? Be very precise and complete in your explanation.

Accepted Answer

(.45)²= 20% of the va

Question 5

In a study concerned with the relationship between X and Y, it is found that 9% of the variance in Y is associated with X. This rXY must have been

Accepted Answer

A)  .09 
B)  .30 
C)  .81 
D)  .08 
A)  .09 
B)  .30 
C)  .81 
D)  .08

Question 6

In general, an increase of .10 points in the correlation coefficient has

Accepted Answer

A)  the greatest consequence for
  
B)  the greatest consequence for
  
C)  the greatest consequence for
  
D)  equal consequence for all above values of r 
A)  the greatest consequence for
  
B)  the greatest consequence for
  
C)  the greatest consequence for
  
D)  equal consequence for all above values of r

Question 7

In which situation does the phenomenon of regression on the mean not occur?

Accepted Answer

A) 
  
B) 
  
C)  r is between 0 and -1.00 
D)  r is between 0 and +1.00 
A) 
  
B) 
  
C)  r is between 0 and -1.00 
D)  r is between 0 and +1.00

Question 8

Fifty percent of Y variance is associated with variation in X when r is approximately

Accepted Answer

A)  .9 
B)  .7 
C)  .5 
D)  .25 
A)  .9 
B)  .7 
C)  .5 
D)  .25

Question 9

If   this means that

Accepted Answer

A)  75% of Y variance is associated with variation in X 
B)  25% of Y variance is associated with variation in X 
C)  variability of predictive error is 75% of what it would be if r were zero 
D)  variability of predictive error is 25% of what it would be if r were zero 
A)  75% of Y variance is associated with variation in X 
B)  25% of Y variance is associated with variation in X 
C)  variability of predictive error is 75% of what it would be if r were zero 
D)  variability of predictive error is 25% of what it would be if r were zero

Question 10

What is meant by regression toward the mean? Give several examples.

Accepted Answer

Consider a group of individuals all with

Question 11

If a regression equation reads:   we know that

Accepted Answer

A)  Y increases 1 unit for every 2 units of increase in X 
B)  Y increases 2 units for every 1 unit of increase in X 
C)    is 3 units lower than X 
D)  the correlation is negative 
A)  Y increases 1 unit for every 2 units of increase in X 
B)  Y increases 2 units for every 1 unit of increase in X 
C)    is 3 units lower than X 
D)  the correlation is negative

Question 12

The amount of regression on the mean is least when r is

Accepted Answer

A)  low 
B)  high 
C)  negative 
D)  positive 
A)  low 
B)  high 
C)  negative 
D)  positive

Question 13

In a study, the correlation between height of parents and height of adult children was found to be +.61. The summary statistics for the group of children are:   in. and SX = 3.1 in. 
(a) What percent of the children's height variance is associated with variation in parent height, and what percent is associated with other factors? 
(b) Compute the amount of children's height variance associated with variation in parent height and the amount associated with other factors. 
(c) In practice, which results would we normally be more interested in, those from (a) or those from (b) ? Why?

Accepted Answer

(a)37% and 63% 
(b)associated with varia

Question 14

A large value of   may be expected when r is

Accepted Answer

A)  +.90 
B)  +.25 
C)  -.75 
D)  -1.00 
A)  +.90 
B)  +.25 
C)  -.75 
D)  -1.00

Question 15

Assume a moderate positive r between father's height and son's adult height. For a father whose height is one standard deviation below the mean, we predict that his son's height will be

Accepted Answer

A)  more than one standard deviation below the mean 
B)  one standard deviation below the mean 
C)  less than one standard deviation below the mean 
D)  at the mean 
A)  more than one standard deviation below the mean 
B)  one standard deviation below the mean 
C)  less than one standard deviation below the mean 
D)  at the mean

Question 16

If   this means that

Accepted Answer

A)  75% of Y variance is associated with variation in X 
B)  25% of Y variance is associated with variation in X 
C)  variability of predictive error is 75% of what it would be if r were zero 
D)  variability of predictive error is 25% of what it would be if r were zero 
A)  75% of Y variance is associated with variation in X 
B)  25% of Y variance is associated with variation in X 
C)  variability of predictive error is 75% of what it would be if r were zero 
D)  variability of predictive error is 25% of what it would be if r were zero

Question 17

If a regression equation reads: we know that

Accepted Answer

A)    is greater than   
B)  SY is greater than SX 
C)  the correlation is negative 
D)  a mistake has been made in calculating r 
A)    is greater than   
B)  SY is greater than SX 
C)  the correlation is negative 
D)  a mistake has been made in calculating r

Question 18

According to their grade on the first midterm, an instructor identifies the 10 best students among his class of 100. Their average grade is A-. After the next examination he reviews their performance. He will probably find that their average grade on the second test will be

Accepted Answer

A)  higher 
B)  about the same 
C)  lower, but above average 
D)  about average 
A)  higher 
B)  about the same 
C)  lower, but above average 
D)  about average

Question 19

will be zero when

Accepted Answer

A) 
  
B) 
  
C) 
  
D) 
  
A) 
  
B) 
  
C) 
  
D)

Question 20

will be zero when

Accepted Answer

A) 
  
B) 
  
C) 
  
D) 
  
A) 
  
B) 
  
C) 
  
D)

The reason that regression on the mean does not result in all individuals being of average stature after several generations is that

measures variation of

If a regression equation reads: we know that

In a study concerned with the relationship between X and Y, it is found that 9% of the variance in Y is associated with X. This r_XY must have been

In general, an increase of .10 points in the correlation coefficient has

In which situation does the phenomenon of regression on the mean not occur?

Fifty percent of Y variance is associated with variation in X when r is approximately

If this means that

What is meant by regression toward the mean? Give several examples.

If a regression equation reads: we know that

The amount of regression on the mean is least when r is

A large value of may be expected when r is

Assume a moderate positive r between father's height and son's adult height. For a father whose height is one standard deviation below the mean, we predict that his son's height will be

If this means that

If a regression equation reads: we know that

According to their grade on the first midterm, an instructor identifies the 10 best students among his class of 100. Their average grade is A-. After the next examination he reviews their performance. He will probably find that their average grade on the second test will be

will be zero when

will be zero when

Introduction

Frequency Distributions, Percentiles,

Graphic Representation of Frequency Distributions

Central Tendency

Variability and Standard Z Scores

Standard Scores and the Normal Curve

Correlation

Prediction

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 9: Interpretive Aspects of Correlation and Regression

The reason that regression on the mean does not result in all individuals being of average stature after several generations is that

measures variation of

If a regression equation reads: we know that

In a study concerned with the relationship between X and Y, it is found that 9% of the variance in Y is associated with X. This rXY must have been

In general, an increase of .10 points in the correlation coefficient has

In which situation does the phenomenon of regression on the mean not occur?

Fifty percent of Y variance is associated with variation in X when r is approximately

If this means that

What is meant by regression toward the mean? Give several examples.

If a regression equation reads: we know that

The amount of regression on the mean is least when r is

A large value of may be expected when r is

Assume a moderate positive r between father's height and son's adult height. For a father whose height is one standard deviation below the mean, we predict that his son's height will be

If this means that

If a regression equation reads: we know that

According to their grade on the first midterm, an instructor identifies the 10 best students among his class of 100. Their average grade is A-. After the next examination he reviews their performance. He will probably find that their average grade on the second test will be

will be zero when

will be zero when

Introduction

Frequency Distributions, Percentiles,

Graphic Representation of Frequency Distributions

Central Tendency

Variability and Standard Z Scores

Standard Scores and the Normal Curve

Correlation

Prediction

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

In a study concerned with the relationship between X and Y, it is found that 9% of the variance in Y is associated with X. This r_XY must have been