1. The value of SS residual measures the average squared distance between the ac

Question

1.

The value of SSresidual measures the average squared distance between the actual Y values and the Y values predicted by the regression equation.

True or false

2.

For linear regression with one predictor variable, what is the value for degrees of freedom for the predicted portion of the Y-score variance, MSregression?

n - 1

2

1

n - 2

3.For either linear regression or multiple regression, the standard error of estimate can be computed

the square root of MSregression

the square root of MSresidual

MSresidual/(n - 2)

MSregression/(n - 2)

4.The Pearson correlation between X1 and Y is r = 0.40. When a second variable, X2, is added to the regression equation, we obtain R2 = 0.64. How much additional variance for the Y scores is predicted by adding the second variable compared to using X1 alone?

0.40 or 40%

0.16 or 16%

0.64 or 64%

0.48 or 48%

5. A Pearson correlation of r = +1.00 between X and Y indicates ____.

All of the other 3 choices occur with a correlation of +1.00.

every change in X causes a change in Y

every increase in X causes an increase in Y

each time X increases, there is a perfectly predictable increase in Y

6.If the following scores are converted to ranks, what values should be assigned to the two individuals who started with scores of X = 5?
     Scores: 2, 3, 5, 5, 7, 10, 18

one receives a rank of 3 and the other gets a rank of 4

both should receive a rank of 4

both should receive a rank of 3

both should receive a rank of 3.5

Explanation / Answer

Solution:-

1) True

2) option D . n - 2

3) option C .  MSresidual/(n - 2)

4) option B.  0.16 or 16%

5) option D. each time X increases, there is a perfectly predictable increase in Y

6) option C. both should receive a rank of 3

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