1. A nurse is interested in whether there is a relationship between daily levels of stress and likelihood of a heart attack. The stress scores (predictor variable) and risk of heart attack values (criterion variable) from a small sample of participants are depicted below (Values below are valid for this question only!)
Stress Score Risk of Heart Attack
(Higher values = more stress) (Higher values = greater risk)
2 0
4 0
4 0
9 6
What is the covariance?

2. A nurse is interested in whether there is a relationship between daily levels of stress and likelihood of a heart attack. The stress scores (predictor variable) and risk of heart attack values (criterion variable) from a small sample of participants are depicted below (Values below are valid for this question only!)
Stress Score Risk of Heart Attack
(Higher values = more stress) (Higher values = greater risk)
9 1
0 8
3 6
3 3
What is the standard deviation of the predictor variable?

3. A nurse is interested in whether there is a relationship between daily levels of stress and likelihood of a heart attack. The stress scores (predictor variable) and risk of heart attack values (criterion variable) from a small sample of participants are depicted below. (Values below are valid for this question only!)
Stress Score Risk of Heart Attack
(Higher values = more stress) (Higher values = greater risk)
1 8
5 2
6 4
9 0
What is the standard deviation of the criterion variable?

4. A nurse is interested in whether there is a relationship between daily levels of stress and likelihood of a heart attack. The stress scores (predictor variable) and risk of heart attack values (criterion variable) from a small sample of participants are depicted below. (Values below are valid for this question only!)
Stress Score Risk of Heart Attack
(Higher values = more stress) (Higher values = greater risk)
3 8
5 0
9 1
2 6
What is the Pearson's r value?

5. A nurse is interested in whether there is a relationship between daily levels of stress and likelihood of a heart attack. The stress scores (predictor variable) and risk of heart attack values (criterion variable) from a small sample of participants are depicted below. (Values below are valid for this question only!)
Stress Score Risk of Heart Attack
(Higher values = more stress) (Higher values = greater risk)
5 1
6 3
2 3
4 6
What is the numeric value of the slope (b)?

6. A nurse is interested in whether there is a relationship between daily levels of stress and likelihood of a heart attack. The stress scores (predictor variable) and risk of heart attack values (criterion variable) from a small sample of participants are depicted below. (Values below are valid for this question only!)
Stress Score Risk of Heart Attack
(Higher values = more stress) (Higher values = greater risk)
4 7
3 2
0 4
1 0
What is the numeric value of the y-intercept (a)?

7. A nurse is interested in whether there is a relationship between daily levels of stress and likelihood of a heart attack. The stress scores (predictor variable) and risk of heart attack values (criterion variable) from a small sample of participants are depicted below. (Values below are valid for this question only!)
Stress Score Risk of Heart Attack
(Higher values = more stress) (Higher values = greater risk)
6 0
5 9
8 3
0 1
Set up the regression equation and use to predict the risk of heart attack for a person with a stress score of 6. The risk of heart attack predicted for a person with a stress score of 6 is?

8. Grade (in terms of the percentage of correct responses) in Psy 1110 is used to predict nurses' salaries and the regression equation turns out to be
ŷ = 7(X) + 328
If a nurse gets 80% correct, his/her predicted salary would be $____00.00? (Fill in the blank with the numbers only from solving the regression equation.)

Answer

9. Grade (in terms of the percentage of correct responses) in Psy 1110 is used to predict nurses' salaries and the regression equation turns out to be
ŷ = 8(X) + 364
If a nurse's predicted salary is eighty-nine thousand (for puposes of this problem, represented numerically as 890), what would be his or her grade in Psy 1110. (Fill in the blank with the numbers only from solving the regression equation.)

Answer

10. A variable that can be used to predict the value of another variable is called

Answer

predictor variable
criterion variable
continuous variable
discrete variable

11. Which of the following correlations is weakest?

Answer

-1
-.5
0
+1

12. Consider the following sets of variables. When is computing correlation appropriate?

Answer

Weight and height
Gender and height
Age (11-20, 21-30, …) and height
Name and height

13. The direction of causality

Answer

Can be determined when two variables have significant linear correlation
Can be determined when two variables have significant nonlinear correlation
Can be determined when two variables have no correlation
Cannot be determined based on correlation alone

14. In a study of how late people are to work, 94% of the variability of the amount of time late could be accounted for by the time spent in traffic jams. What was the correlation coefficient?

15.

If you were to compute a correlation between the X and Y variables for each of the three sets of data, which set of data would yield a correlation closest to zero?

Answer

A
B
C

16. If you were to construct a regression equation using the X variable to predict the Y variable for each of the three sets of data, for which set of data would the regression equation have the largest, positive slope?

Answer

A
B
C

17. If you were to construct a regression equation using the X variable to predict the Y variable for each of the three sets of data, for which set of data would the regression equation have the most negative slope?

Answer

A
B
C

18. Critical thinking question! Which of the following is the best characterization of the data pattern (between viewing violent TV programming and subsequent aggressive behavior) depicted in the figure below? (Each dot represents a child's level on each of the variables, with higher values indicating more aggression and more exposure to viewing violence.)

positive correlation
negative correlation
no correlation
insufficient variability to properly assess correlation

19. Let us say, hypothetically, that you found a significant positive correlation between Exposure to TV Violence and Aggressive Behavior. Which of the following might explain this relationship?
Select any and all options that are correct.

Answer

Greater exposure to TV violence leads to less aggressive behavior
Greater exposure to TV violence leads to more aggressive behavior
Exposure to TV violence and aggressive behavior are unrelated
More aggressive behavior leads to greater exposure to TV violence
A third unknown variable is causing both aggressive behavior and exposure to TV violence to similarly rise and fall.