Question 1

The   
transformation yields values of 
   
 for corresponding values of r which are

Accepted Answer

A)  increasingly larger than r as r becomes larger 
B)  increasingly smaller than r as r becomes larger 
C)  proportionately larger than r 
D)  proportionately smaller than r 
A)  increasingly larger than r as r becomes larger 
B)  increasingly smaller than r as r becomes larger 
C)  proportionately larger than r 
D)  proportionately smaller than r A

Question 2

When n is very large, we may find that

Accepted Answer

A)  the standard error of the sampling distribution cannot be determined 
B)  large values of r may suggest that we should retain the hypothesis that   when it is false 
C)  the sampling distribution departs substantially from a normal distribution 
D)  the correlation coefficient is shown to be significantly different from zero when in fact the true value of   is not importantly different from zero 
A)  the standard error of the sampling distribution cannot be determined 
B)  large values of r may suggest that we should retain the hypothesis that   when it is false 
C)  the sampling distribution departs substantially from a normal distribution 
D)  the correlation coefficient is shown to be significantly different from zero when in fact the true value of   is not importantly different from zero D

Question 3

The problem that makes the inference about correlation coefficients somewhat less straightforward than inference about means is that the sampling distribution of r

Accepted Answer

A)  has an unknown mean 
B)  has an unknown standard deviation 
C)  varies in shape according to circumstance 
D)  is bimodal because r can be negative as well as positive 
A)  has an unknown mean 
B)  has an unknown standard deviation 
C)  varies in shape according to circumstance 
D)  is bimodal because r can be negative as well as positive C

Question 4

You read in a review article: "Milhous (1979) found a significant positive correlation between peer ratings of self-confidence and scores on the Milhous Self Confidence Scale for a large sample of college sorority members."
(a)How might such a statement be misinterpreted by the statistically unsophisticated reader
(b)What does the statement really mean? Be precise in your answer. Use appropriate symbols and statistical terminology
(c)What single piece of additional information would be most necessary to an adequate interpretation of Milhous' results?

Accepted Answer

(a)Misinterpreted as a large o

Question 5

The standard error of   
is

Accepted Answer

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

Question 6

For each of the following cases, give the size of the sample r required for statistical significance:
(a)
   one-tailed test;

(b) 
    two-tailed test;
(c) 
   two-tailed test;
(d)
    two-tailed test;

(e) 
   one-tailed test.

Accepted Answer

(a).805
(b

Question 7

In which of the following cases could the sample r have been any value over a range from rather small to quite large?

Accepted Answer

A)  significant r,   
B)  significant r,   
C)  nonsignificant r,   
D)  any of the above 
A)  significant r,   
B)  significant r,   
C)  nonsignificant r,   
D)  any of the above

Question 8

The human resources director of a large bank conducts a study to evaluate a particular employment test for possible use in screening prospective applicants for the position of teller. A group of 16 applicants is administered the test, hired, and rated by their supervisors after 6 months on the job. A sample correlation of +.39 is obtained between test scores and supervisors' ratings. Use a significance testing approach to evaluate the sample result ($\alpha$= .05).

Accepted Answer

@#IMG-DLM&  from Ta

Question 9

If we want to know whether a test is predictive of success according to a given performance criterion, we can be certain that it is to some degree if r between these two variables is

Accepted Answer

A)  +.25 
B)  +.50 
C)  +.75 
D)  without knowledge of n, we cannot be certain in any of these circumstances 
A)  +.25 
B)  +.50 
C)  +.75 
D)  without knowledge of n, we cannot be certain in any of these circumstances

Question 10

The sampling distribution of r is most nearly normal when   
 is

Accepted Answer

A)  positive 
B)  negative 
C)  near ±1.00 
D)  near zero 
A)  positive 
B)  negative 
C)  near ±1.00 
D)  near zero

Question 11

To test the hypothesis that   
 we need to remember that the number of degrees of freedom is

Accepted Answer

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

Question 12

The test of a hypothesis about correlation coefficients is probably most frequently used to inquire whether

Accepted Answer

A)    is zero 
B)    is some specified value other than zero 
C)  there is a difference between   's obtained from independent samples 
D)  there is a difference between   's obtained from dependent samples 
A)    is zero 
B)    is some specified value other than zero 
C)  there is a difference between   's obtained from independent samples 
D)  there is a difference between   's obtained from dependent samples

Question 13

We can be fairly sure that   
is very small in which of the following cases?

Accepted Answer

A)  significant r,   
B)  nonsignificant r,   
C)  nonsignificant r,   
D)  none of the above 
A)  significant r,   
B)  nonsignificant r,   
C)  nonsignificant r,   
D)  none of the above

Question 14

A nonsignificant correlation is obtained for a random sample of 6 cases. From this we can infer that

Accepted Answer

A)    
B)    is very small 
C)    does not differ by an important amount from 0 
D)  none of the above 
A)    
B)    is very small 
C)    does not differ by an important amount from 0 
D)  none of the above

Question 15

A significant correlation indicates a conclusion that

Accepted Answer

A)    is large 
B)  r is large 
C)    is not zero 
D)  r is not zero 
A)    is large 
B)  r is large 
C)    is not zero 
D)  r is not zero

Question 16

Values of r vary more when

Accepted Answer

A)  n is small 
B)    is low 
C)  n is small and   is low 
D)  n is small and   is high 
A)  n is small 
B)    is low 
C)  n is small and   is low 
D)  n is small and   is high

Question 17

If the   
transformation is used to evaluate inference about correlation coefficients, the referent distribution is

Accepted Answer

A)  the normal distribution 
B)  Student's distribution of t 
C)  dependent on the number of degrees of freedom 
D)  a rectangular distribution 
A)  the normal distribution 
B)  Student's distribution of t 
C)  dependent on the number of degrees of freedom 
D)  a rectangular distribution

Question 18

When   
, the sampling distribution of r is

Accepted Answer

A)  skewed negatively 
B)  skewed positively 
C)  symmetrical 
D)  normal when   
A)  skewed negatively 
B)  skewed positively 
C)  symmetrical 
D)  normal when

Question 19

is to the sampling distribution of r as ____________ is to the sampling distribution of the mean.

Accepted Answer

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

Question 20

The purpose of the   
transformation is to correct for

Accepted Answer

A)  an unknown mean of the sampling distribution of r 
B)  an unknown standard deviation of the sampling distribution of r 
C)  varying shape of the sampling distribution of r 
D)  differing values of n 
A)  an unknown mean of the sampling distribution of r 
B)  an unknown standard deviation of the sampling distribution of r 
C)  varying shape of the sampling distribution of r 
D)  differing values of n

The transformation yields values of for corresponding values of r which are

When n is very large, we may find that

The problem that makes the inference about correlation coefficients somewhat less straightforward than inference about means is that the sampling distribution of r

The standard error of is

For each of the following cases, give the size of the sample r required for statistical significance: (a) one-tailed test; (b) two-tailed test; (c) two-tailed test; (d) two-tailed test; (e) one-tailed test.

In which of the following cases could the sample r have been any value over a range from rather small to quite large?

If we want to know whether a test is predictive of success according to a given performance criterion, we can be certain that it is to some degree if r between these two variables is

The sampling distribution of r is most nearly normal when is

To test the hypothesis that we need to remember that the number of degrees of freedom is

The test of a hypothesis about correlation coefficients is probably most frequently used to inquire whether

We can be fairly sure that is very small in which of the following cases?

A nonsignificant correlation is obtained for a random sample of 6 cases. From this we can infer that

A significant correlation indicates a conclusion that

Values of r vary more when

If the transformation is used to evaluate inference about correlation coefficients, the referent distribution is

When , the sampling distribution of r is

is to the sampling distribution of r as ____________ is to the sampling distribution of the mean.

The purpose of the transformation is to correct for

Introduction

Frequency Distributions, Percentiles,

Graphic Representation of Frequency Distributions

Central Tendency

Variability and Standard Z Scores

Standard Scores and the Normal Curve

Correlation

Prediction

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

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 16: Inference About Correlation Coefficients

The transformation yields values of for corresponding values of r which are

When n is very large, we may find that

The problem that makes the inference about correlation coefficients somewhat less straightforward than inference about means is that the sampling distribution of r

The standard error of is

For each of the following cases, give the size of the sample r required for statistical significance: (a) one-tailed test; (b) two-tailed test; (c) two-tailed test; (d) two-tailed test; (e) one-tailed test.

In which of the following cases could the sample r have been any value over a range from rather small to quite large?

If we want to know whether a test is predictive of success according to a given performance criterion, we can be certain that it is to some degree if r between these two variables is

The sampling distribution of r is most nearly normal when is

To test the hypothesis that we need to remember that the number of degrees of freedom is

The test of a hypothesis about correlation coefficients is probably most frequently used to inquire whether

We can be fairly sure that is very small in which of the following cases?

A nonsignificant correlation is obtained for a random sample of 6 cases. From this we can infer that

A significant correlation indicates a conclusion that

Values of r vary more when

If the transformation is used to evaluate inference about correlation coefficients, the referent distribution is

When , the sampling distribution of r is

is to the sampling distribution of r as ____________ is to the sampling distribution of the mean.

The purpose of the transformation is to correct for

Introduction

Frequency Distributions, Percentiles,

Graphic Representation of Frequency Distributions

Central Tendency

Variability and Standard Z Scores

Standard Scores and the Normal Curve

Correlation

Prediction

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

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