Question 1

What is regression typically used for?

Accepted Answer

A) The researcher uses it to find the statistical significance of correlations. 
B) The researcher uses it to convert raw scores to t scores. 
C) The researcher uses it to make predictions about scores based on other scores. 
D) The researcher uses it to create linear relationships for transforms. 
A) The researcher uses it to find the statistical significance of correlations. 
B) The researcher uses it to convert raw scores to t scores. 
C) The researcher uses it to make predictions about scores based on other scores. 
D) The researcher uses it to create linear relationships for transforms. C

Question 2

Assume that X and Y correlate .4, are in Z score form, and that a particular value of X is 1. What is the predicted value of Y ?

Accepted Answer

A) 0 
B) .4 
C) .6 
D) 1 
A) 0 
B) .4 
C) .6 
D) 1 B

Question 3

Describe the difference between correlation and regression. What are the advantages and disadvantages of each method of assessing bivariate relationships?

Accepted Answer

Correlation and regression are both statistical methods used to assess the relationship between two variables. However, they have different purposes and provide different types of information.

Correlation measures the strength and direction of the relationship between two variables. It ranges from -1 to 1, with 1 indicating a perfect positive relationship, -1 indicating a perfect negative relationship, and 0 indicating no relationship. Correlation does not imply causation, meaning that just because two variables are correlated does not mean that one causes the other.

On the other hand, regression is used to predict the value of one variable based on the value of another variable. It provides information about the strength and direction of the relationship, as well as the ability to make predictions. Regression can also be used to test hypotheses about the relationship between variables.

The advantages of correlation include its simplicity and ease of interpretation. It provides a clear indication of the strength and direction of the relationship between variables. However, correlation does not provide information about the ability to predict one variable based on the other.

The advantages of regression include its ability to make predictions and test hypotheses about the relationship between variables. It provides more detailed information about the relationship and allows for the identification of potential causal relationships. However, regression can be more complex and may require more assumptions about the data.

The disadvantages of correlation include its inability to make predictions and its lack of information about causation. It also does not provide information about the ability to predict one variable based on the other.

The disadvantages of regression include its complexity and the potential for overfitting the data. It also requires more assumptions about the data and may be more difficult to interpret for those without a strong statistical background.

In summary, correlation and regression are both valuable methods for assessing bivariate relationships, but they provide different types of information and have different strengths and limitations. The choice of method depends on the specific research question and the goals of the analysis.

Question 4

If the line that comes closest to all points in a scatter diagram is perfectly straight, the correlation between the two variables is

Accepted Answer

A) linear. 
B) curvilinear. 
C) positive. 
D) unknown. 
A) linear. 
B) curvilinear. 
C) positive. 
D) unknown.

Question 5

The coefficient of determination is the

Accepted Answer

A) number of degrees of freedom. 
B) difference between predicted and observed values of Y . 
C) mean. 
D) squared correlation coefficient. 
A) number of degrees of freedom. 
B) difference between predicted and observed values of Y . 
C) mean. 
D) squared correlation coefficient.

Question 6

If the correlation between X and Y is .60 and we observe a score of 1.0 ( Z units)on X , what score would be predicted for Y ?

Accepted Answer

A) −1.2 
B) 0 
C) 0.6 
D) 1.6 
A) −1.2 
B) 0 
C) 0.6 
D) 1.6

Question 7

The standard deviation of the residuals is called the

Accepted Answer

A) coefficient of alienation. 
B) shrinkage. 
C) coefficient of determination. 
D) standard error of estimate. 
A) coefficient of alienation. 
B) shrinkage. 
C) coefficient of determination. 
D) standard error of estimate.

Question 8

A correlation coefficient of −.67 tells us

Accepted Answer

A) the magnitude of the correlation only. 
B) the direction of the correlation only. 
C) the magnitude and direction of the correlation. 
D) neither the magnitude nor the direction of the correlation. 
A) the magnitude of the correlation only. 
B) the direction of the correlation only. 
C) the magnitude and direction of the correlation. 
D) neither the magnitude nor the direction of the correlation.

Question 9

A regression equation was derived from a small sample in which X and Y are correlated .6. The equation is Y ´ = .6 X + 15. Suppose this equation were applied to a second sample. It is likely that the correlation between the scores predicted from this equation and the observed scores will be

Accepted Answer

A) 0 
B) less than 0.6. 
C) approximately 0.6. 
D) greater than 0.6. 
A) 0 
B) less than 0.6. 
C) approximately 0.6. 
D) greater than 0.6.

Question 10

Owning a dog may make people happier. Then again, happier people may be more likely to want a dog. Not knowing whether happiness leads to dog ownership or vice versa, we have

Accepted Answer

A) restricted range. 
B) the correlation-causation problem. 
C) cross-validation. 
D) shrinkage. 
A) restricted range. 
B) the correlation-causation problem. 
C) cross-validation. 
D) shrinkage.

Question 11

Which of the following is computed to show the relationship between two artificially dichotomous variables?

Accepted Answer

A) Tetrachoric correlation 
B) Factor analysis 
C) Discriminant analysis 
D) Multiple regression 
A) Tetrachoric correlation 
B) Factor analysis 
C) Discriminant analysis 
D) Multiple regression

Question 12

Which of the following is an artificially dichotomous variable?

Accepted Answer

A) Favorite ice cream flavor 
B) Weight 
C) Success (pass/fail)on a final exam 
D) GPA 
A) Favorite ice cream flavor 
B) Weight 
C) Success (pass/fail)on a final exam 
D) GPA

Question 13

Explain the correlation-causation problem and give an example.

Accepted Answer

The correlation-causation problem refers

Question 14

The best-fitting straight line through a set of points in a scatter diagram is known as the

Accepted Answer

A) regression line. 
B) linear line. 
C) correlation line. 
D) perfect correlation. 
A) regression line. 
B) linear line. 
C) correlation line. 
D) perfect correlation.

Question 15

One formula for the correlation between a continuous variable and an artificially dichotomized variable is

Accepted Answer

A) Spearman's rank order formula. 
B) the point biserial correlation. 
C) the phi coefficient. 
D) the biserial correlation. 
A) Spearman's rank order formula. 
B) the point biserial correlation. 
C) the phi coefficient. 
D) the biserial correlation.

Question 16

The difference between the observed and predicted score is

Accepted Answer

A) the residual. 
B) the intercept. 
C) the Z score. 
D) correlation coefficient. 
A) the residual. 
B) the intercept. 
C) the Z score. 
D) correlation coefficient.

Question 17

The sum of the squared deviations around the mean will be ______ it is around any value other than the mean.

Accepted Answer

A) more than 
B) less than 
C) the same as 
D) more or less, but never the same as 
A) more than 
B) less than 
C) the same as 
D) more or less, but never the same as

Question 18

Each point on a scatter diagram shows

Accepted Answer

A) the variance of a set of scores. 
B) the standard deviation of a set of scores. 
C) where an individual scored compared to the mean. 
D) where an individual scored on both X and Y . 
A) the variance of a set of scores. 
B) the standard deviation of a set of scores. 
C) where an individual scored compared to the mean. 
D) where an individual scored on both X and Y .

Question 19

Which of the following correlations represents the strongest relationship between two variables?

Accepted Answer

A) −.85 
B) .01 
C) .50 
D) .80 
A) −.85 
B) .01 
C) .50 
D) .80

Question 20

An appropriate correlation coefficient to show the relationship between two artificially dichotomous variables is the

Accepted Answer

A) biserial correlation. 
B) phi coefficient. 
C) tetrachoric correlation. 
D) point biserial correlation. 
A) biserial correlation. 
B) phi coefficient. 
C) tetrachoric correlation. 
D) point biserial correlation.

Exam 3: Correlation and Regression

What is regression typically used for?

Assume that X and Y correlate .4, are in Z score form, and that a particular value of X is 1. What is the predicted value of Y ?

Describe the difference between correlation and regression. What are the advantages and disadvantages of each method of assessing bivariate relationships?

If the line that comes closest to all points in a scatter diagram is perfectly straight, the correlation between the two variables is

The coefficient of determination is the

If the correlation between X and Y is .60 and we observe a score of 1.0 ( Z units)on X , what score would be predicted for Y ?

The standard deviation of the residuals is called the

A correlation coefficient of −.67 tells us

A regression equation was derived from a small sample in which X and Y are correlated .6. The equation is Y ´ = .6 X + 15. Suppose this equation were applied to a second sample. It is likely that the correlation between the scores predicted from this equation and the observed scores will be

Owning a dog may make people happier. Then again, happier people may be more likely to want a dog. Not knowing whether happiness leads to dog ownership or vice versa, we have

Which of the following is computed to show the relationship between two artificially dichotomous variables?

Which of the following is an artificially dichotomous variable?

Explain the correlation-causation problem and give an example.

The best-fitting straight line through a set of points in a scatter diagram is known as the

One formula for the correlation between a continuous variable and an artificially dichotomized variable is

The difference between the observed and predicted score is

The sum of the squared deviations around the mean will be ______ it is around any value other than the mean.

Each point on a scatter diagram shows

Which of the following correlations represents the strongest relationship between two variables?

An appropriate correlation coefficient to show the relationship between two artificially dichotomous variables is the

Introduction

Norms and Basic Statistics for Testing

Reliability

Validity

Writing and Evaluating Test Items

Test Administration

Interviewing Techniques

Theories of Intelligence and the Binet Scales

The Wechsler Intelligence Scales: Wais-Iv, Wisc-Iv, and Wppsi-III

Testing in Education: Tests of Ability in Education and Special Education

Standardized Tests in Education, Civil Service, and the Military

Applications in Clinical and Counseling Settings

Projective Personality Tests

Computers and Basic Psychological Science in Testing

Testing in Counseling Psychology

Testing in Health Psychology and Health Care

Testing in Industrial and Business Settings

Test Bias

Testing and the Law

The Future of Psychological Testing

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