Chapter 3

Question 1

variable

Answer 1

measure that can have more than one value

Question 2

correlation coefficient

Answer 2

is a mathematical index that describes the direction and magnitude of a relationship.

Question 3

positive correlations

Answer 3

in which if the value of one variable goes up the value of the other rises also.

Question 4

negative correlations

Answer 4

when the value of one variable rises, the value of the other falls.

Question 5

The Regression Line

Answer 5

the best straight line through a set of points in a scatter diagram.

Question 6

homogeneity of variance

Answer 6

if all random variables in the sequence or vector have the same finiteif all random variables in the sequence or vector have the same finite variance.

Question 7

regression line describes

Answer 7

the best linear relation between the X and Y scores

Question 8

Covariance

Answer 8

the extent to which knowing the value of one variable predicts the value of the other

Question 9

regression coefficient

Answer 9

The slope of the regression line

Question 10

slope

Answer 10

This describes how much change is expected in Y each time X changes by one unit
- X = bY

Question 11

intercept

Answer 11

a, is the value of Y when X = 0. That’s where the regression line crosses the Y axis.
- a = Y – b X

Question 12

residual

Answer 12

the difference between an actual score and the predicted score (predicted by the regression line)

Question 13

principle of least squares

Answer 13

The best-fitting line keeps residuals to a minimum

Question 14

Correlation

Answer 14

is a special case of regression in which the scores of both variables are in standardized, or Z, units
- the intercept is always 0 (must be continuous)

Question 15

difference between regression and correlation

Answer 15

In correlation, both scores (X and Y) have been converted to Z scores, so they both have mean of zero. Thus the intercept between the X and Y axes will always be at 0.

Question 16

Pearson product moment correlation coefficient (r)

Answer 16

is a ratio used to determine the degree of variation in one variable that can be estimated from knowledge about variation in the other variable.

Question 17

null hypothesis

Answer 17

there is no real relationship between the variables in question

Question 18

criterion validity evidence

Answer 18

the relationship between a test score and some well-defined criterion, such as scores on a job aptitude test and actual job performance

Question 19

Spearman’s rho (ρ)

Answer 19

is used to find the association between two sets of ranks (second, third, fourth, etc.)

Question 20

dichotomous

Answer 20

variables that can have only two values, like yes-no, correct-incorrect

Question 21

Biserial correlation

Answer 21

expresses the relationship between a continuous variable and an artificial dichotomous variable.

Question 22

point biserial correlation, phi (φ) coefficient.

Answer 22

If one variable is a continuous variable and the other is a true dichotomous variable (can have only one of two possible values

Question 23

tetrachoric correlation.

Answer 23

if both variables are artificially dichotomous variables

Question 24

Residual:

Answer 24

The difference between the observed and the predicted values

Question 25

Standard Error of Estimate:

Answer 25

The standard deviation of the residuals

Question 26

Coefficient of Determination:

Answer 26

The correlation coefficient squared`

Question 27

Coefficient of Alienation:

Answer 27

is a measure of the nonassociation between two variables!

Question 28

Shrinkage

Answer 28

the amount of decrease observed when a regression equation is created for one population and then applied to another.

Question 29

Cross Validation

Answer 29

Using the regression equation derived using one group of subjects to predict performance in a different group of subjects

Question 30

The Correlation-Causation Problem:

Answer 30

Just because two variables are correlated does not mean that one of them caused the variation in the other!

Question 31

Third Variable Explanation

Answer 31

Some third (unobserved) variable caused the variation in both of the other variables.

Question 32

Restricted Range

Answer 32

If the variability of a variable is extremely restricted, significant correlations may be difficult to find even if they may actually be there.

Question 33

Multivariate analysis

Answer 33

considers the relationship among combinations of three or more variables

Question 34

Discriminant analysis

Answer 34

the linear combination of variables that provides the maximum discrimination between categories

Question 35

Factor Analysis:

Answer 35

correlation between every variable and every other variable.