# When there are two predictor variables, R2 is the simple sum

? Question 1 10 out of 10 points

When there are two predictor variables, R2 is the simple sum of r2 for the relationship of the first predictor variable and Y and r2 for the relationship of the second predictor variable and Y.

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? Question 2 10 out of 10 points

If the relationship between two variables is perfect the standard error of estimate equals 0.

? Question 3 10 out of 10 points

For regression purposes, it is customary to assign Y to the variable we are predicting from.

? Question 4 10 out of 10 points

In general one is less confident in predictions of Y when the value of X used for the prediction is outside the range of the original data used to construct the regression line.

? Question 5 0 out of 10 points

For regression purposes, it is customary to assign X to the variable we are predicting from.

? Question 6 10 out of 10 points

When the relationship is perfect, the regression of Y on X is the same as the regression of X on Y.

? Question 7 10 out of 10 points

If we minimize ? (Y?Y’)2, we will minimize the total error of prediction.

? Question 8 0 out of 10 points

The least squares regression line insures the maximum number of direct hits.

? Question 9 10 out of 10 points

The higher the r value, the lower the standard error of estimate.

? Question 10 10 out of 10 points

Using a second predictor variable always increases the accuracy of prediction