This section defines simple linear regression, uses scatter plots to reveal linear patterns, and talks about prediction error. It also discusses how to compute regression line by minimizing squared errors.
Questions
Question 1 out of 7.
The formula for a regression equation is . What would be the predicted
score for a person scoring 4 on
?
Question 2 out of 7.
Suppose it is possible to predict a person's score on Test from the person's score on Test
. The regression equation is:
. What is a person's predicted score on Test
assuming this person got a 40 on Test
?
Question 3 out of 7.
Suppose a person got a score of 32.5 on Test and a score of 95.25 on
Test
.
Using the same regression equation as in the previous problem (
), 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?
The line that goes through the most points
The line that has the same number of points above it as below it
The line that minimizes the sum of squared errors of prediction
Question 5 out of 7.
The mean of is 3 and the mean of
is 7. The regression line that predicts
from
necessarily goes through the point (3,7).
True
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