Quiz 10: Correlation and Regression

Given the regression equation, Y = 5 + 0.5X, where X is a score on an attitude scale and Y is a job satisfaction score, what satisfaction score would be predicted for an attitude score of 20?

15

20

25

30

15

Suppose you calculated a correlation coefficient that was r = 0.12.  What would be an appropriate interpretation?

1. There is a strong, positive correlation.

2. There is a weak, negative correlation.

3. There is a weak, positive correlation.

4. The means of both groups are very similar.

There is a weak, positive correlation.

Suppose that college grade point average and the verbal portion of an IQ test had a correlation of .5. What percent of the variance do those two have in common?

1. 50 percent

2. 25 percent

3. 100 percent

4. 16 percent

25 percent

The effect size index for the correlation coefficient is

b coefficient

r

a coefficient

 predicted y score

r

If you have a regression equation…

1. you know the degree of relationship between the two variables

2. you know the proportion of variance the two variables have in common

3. you can predict a score on one variable if you know a score on the other variable

4. all of the above

You can predict a score on one variable if you know a score on the other variable

In a bivariate distribution, there is/are ______ possible correlation coefficient(s) and ______ possible regression equation(s).

1. one; one

2. two; one

3. two; two

4. one; two

One; two

When two distributions can be aligned with paired sets of scores the result is a   ___  distribution.

1. bimodal

2. bivariate

3. rectangular

4. independent

Bivariate

In the regression equation: y = 30 + 1.5(x), if x was to increase by two units, how much change is expected in y?

30

1.50

3

unable to tell with the current information

3

In the regression equation, which coefficient tells you the value of the dependent variable when x = 0?

1. a coefficient

2. b coefficient

3. r coefficient

4. r-squared coefficient

a coefficient

In simple linear regression, which point always falls on the line of best fit?

1. the Pearson r

2. the b coefficient

3. the mean X and mean of Y

4. all of the observed scores

The mean X and mean of Y

Which of the following statements describes a negative correlation?

1. The more the better.

2. At first practice produces big changes but as time goes on each practice session produces fewer and fewer changes.

3. More I eat the less I weigh.

4. None of these.

More I eat the less I weigh