1. IT OUT!

2. Directions: Students get into pairs, decide A and B
Each pair gets a whiteboard and 2 markers
For each question,one part of the partner writes the answer on the whiteboard solo.
When finished, the other partner CHECKS the work
When pair agrees, hold up the board.
One point per correct answer

3. Question 1- Partner A Interpret the y-intercept.
If the LSRL for days after shaving on beard growth in (mm) is:
Interpret the y-intercept.
Answer: When there are no days after shaving, the predicted beard growth is expected to be about 0.542mm

4. Question 2- Partner B Interpret the slope.
If the LSRL for days after shaving on beard growth in (mm) is:
Interpret the slope.
Answer: On avergae, As the number of days after shaving increases by 1, the predicted beard growth will increase by ABOUT 2.76mm

5. 3(A): If 70% of the variation of a person’s income can be explained by the change in their age, what is the correlation?
A) .49
B) .70
C) .83
D) .92
E) .99
Answer: C

6. 4(B): Which of the following are resistant to outliers?
A) LSRL
B) Correlation
C) Coefficient of Determination
D) Slope
E) None of the above
Answer: E

7. 5(A):Which of the following does not contain an error?
A) The correlation between age and height is 1.18
B) The correlation between gender and age is .87
C) If the correlation between two variables is
-0.98, there is a weak correlation
D) Removing an outlier will always change the correlation
E) If the correlation between x and y is 0.78, then the correlation between y and x is also 0.78
Answer: E

8. 6(B):If the correlation between length of hair and time in takes to wash hair is 0.85, what percent of the variation in time it takes to wash hair can be explained by the linear relationship of time and length of hair?
A) 40%
B) 42.5%
C) 72%
D) 85%
E) 92%
Answer: C

9. 7(A): If r = -0.8 for the LSRL of time it takes to get to Los Angeles from San Diego on speed, interpret the coefficient of determination
Answer: About 64% of the variation in time it takes to get to LA from SD can be explained by the least squares regression of time on speed.

10. 8(B): If r = -0.8 for the LSRL of time it takes to get to Los Angeles from San Diego on speed, interpret the correlation
Answer: Since r = -.8 is fairly close to -1, there is a fairly strong, positive, linear relationship between time it takes to get to LA from SD and speed

11. 9(A): Using the table below, find the LSRL of cholesterol on fat intake
Predictor
Coef
StDev T P
Constant
172.8
22.87
7.52
0.000
Fat intake
41.9
5.35
8.113
Answer: cholesterol(hat) = (fat intake)

12. 10(B): Using the table below, find the correlation of cholesterol on fat intake (grams)
Predictor
Coef
StDev T P
Constant
172.8
22.87
7.52
0.000
Fat intake
41.9
5.35
8.113
Answer: (you know it’s positive since the slope is positive)
s = R-sq = 86.2% R-sq(adj) = 81.1%

13. Question 11(A)
A random sample of students was asked a series of questions to see if study habits can predict GPA. The mean amount of study time per night was 105 minutes with a standard deviation of 22.4 minutes. The mean GPA was 3.46 with a standard deviation of If the correlation between study time and GPA is .75, find the LSRL of GPA on Study time.
Answer: GPA(hat) = (study time)

14. Question 12(B)
A random sample of pro golfers was asked questions to see if practice time can predict golf scores. The mean amount of practice time was 12 hours per week with a standard deviation of 2.5 hours. The mean golf score (on 18 holes) was with a standard deviation of If the correlation between practice time and golf score is -.45, find the LSRL of golf score on practice time.
Answer: golf score(hat) = – (practice time)