Introduction to Linear Regression

Question 1 out of 7.

The formula for a regression equation is \(Y' = 3X - 2\). What would be the predicted \(Y\) score for a person scoring 4 on \(X\)?

Question 2 out of 7.

Suppose it is possible to predict a person's score on Test \(B\) from the person's score on Test \(A\). The regression equation is: \(B' = 2.3A + 9.5\). What is a person's predicted score on Test \(B\) assuming this person got a 40 on Test \(A\)?

Question 3 out of 7.

Suppose a person got a score of 32.5 on Test \(A\) and a score of 95.25 on Test \(B\). Using the same regression equation as in the previous problem (\(B' = 2.3A + 9.5\)), what is the error of prediction for this person?

Question 4 out of 7.

What is the most common criterion used to determine the best-fitting line? 

1. The line that goes through the most points
2. The line that has the same number of points above it as below it
3. The line that minimizes the sum of squared errors of prediction

Question 5 out of 7.

The mean of \(X\) is 3 and the mean of \(Y\) is 7. The regression line that predicts \(Y\) from \(X\) necessarily goes through the point (3,7). 

1. True
2. False

Question 6 out of 7.

You want to be able to predict a woman's shoe size from her height. You have gathered this information from your female classmates. The mean height of women in your class is 64 inches, and the standard deviation is 2 inches. The mean shoe size is 8, and the standard deviation is 1. The correlation between these two variables is .5. What is the slope of the regression line?

Question 7 out of 7.

What is the slope of the regression line when predicting Y from X?

 X	 Y
 10	 11
 16	 16
 13	 14
 10	 12
 12	 12
 13	 10
 11	 12
 11	 11
  9	  9
 10	 12
  8	 12
 13	 12
  8	  8
 10	 12
 12	 12
  8	  8
  6	 11
  8	  7
 12	 13
 13	 10
  6	  9
 13	 12
 12	 10
 13	 12
  8	  9