Bootstrapping and Randomization

StatCrunch Assignment 2 has problems similar to those in your module readings. The purpose of this assignment is to allow you to demonstrate that you are learning how to use the software and to interpret the results you get.
statcrunch_assignment_2__4_.docx

random_sample_of_30_statcrunch_u.docx

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StatCrunch Assignment 2
First save this file to your computer. Answer each of the following questions, then resave the file
along with your answers and turn it in using the assignment link in Module 3, Activity 4. the first
four problems are worth 10 points each. Problems 5 and 6 are worth 30 points each.
1. If the original sample is 48, 55, 43, 61, 39, which of the following would not be a possible
bootstrap sample? Explain why it wouldn’t be.
a) 48, 55, 43, 61, 39
b) 43, 39, 56, 43, 61
c) 55, 48, 55, 48, 61
d) 39, 39, 39, 39, 39
2. The following bootstrap output is for mileage of a random sample of 25 mustang cars.
Based on a 90% confidence interval, which of the following would not be a plausible value of the
population mean, µ? Explain why it wouldn’t be.
a) 60.01
b) 80.01
c) 55
d) 52
3. Which of the following p-values would provide more evidence in support of the alternate
hypothesis and against the null hypothesis? Explain your answer.
a) 0.15
b) 0.85
c) 0.009
d) 0.05
4. In a sample of 56 addicts, 28 were given a new drug to help them overcome their addiction,
while the remaining 28 were given the current drug. The following is the output from a
randomization test for the difference in the proportion of addicts suffering relapses.
a) What is the difference in proportions in the original data?
b) What is the p-value and what does it mean in terms of this specific problem?
In StatCrunch Assignment 1A, you selected a random sample of 30 StatCrunch U students and
gathered some survey data regarding those students. Use the StatCrunch data file you created
to complete the remainder of this assignment.
5. Construct a bootstrap distribution of the credit card debt data from your sample using 3000
resamples.
a) Paste a copy of your distribution here. (With a PC, you can press the control-alt-fn-F11 keys
to copy the window showing the distribution.)
b) What is the mean of your original sample?
c) What is the 95% confidence interval estimate of the population mean obtained from your
bootstrap distribution?
6. Suppose you want to compare the amount of credit card debt for males and females. The null
hypothesis for this problem would be no difference in the mean amount of credit card debt for
males and females and the alternate hypotheses would be that there is a difference in mean
amounts of credit card debt. Conduct a randomization test for two means with 3000
randomizations. (Your input menu should be as follows.)
a) Paste the output from your randomization test here.
b) What is the mean difference in credit card debt of the two groups in the original data?
c) What p-value did you get in your randomization? Explain in the context of the problem what
the p-value means.
d) Do you think the data support the null hypothesis of no difference in mean credit card debt
between males and females or the alternate hypothesis that there is a difference? Explain your
answer.
Sampling Activity Worksheet
The easiest way to proceed from here is to use the Sampling Activity Worksheet shown below
to record the ID numbers of the students in your random sample. Print this page, then go
through your sample and record the numbers.
Write the ID numbers of your sample of size 30 on the sheet below. This will help in the next
step.
1. 1966
16. 29130
2. 6264
17. 30017
3. 7704
18. 30030
4. 8549
19. 30180
5. 8842
20. 32331
6. 9274
21. 33628
8. 12420
22. 36861
7. 13641
23. 37604
9. 14202
24. 37973
10. 16603
25. 38825
11. 16965
26. 40182
12. 18543
27. 42197
13. 21893
28. 42487
14. 23297
29. 43861
15. 25529
30. 44571
Save to your StatCrunch files.
ID
Gender
Class Hours Work Loans CC Debt
1966
Male
2
18
0
0
2317
6264
Male
2
17
16
8282
3168
7704
Male
3
12
0
0
2885
8548
Female
3
14
0
12355 2104
8842
Female
1
15
0
5776
981
9274
Female
1
9
27.5
5029
1163
12420 Female
1
17
16.5
0
1080
13641 Male
14
0
0
2099
14202 Female
2
12
0
0
16603 Female
4
10
23
15650 2941
16965 Male
15
16
15725 2998
18543 Female
3
9
24.5
0
2291
21893 Female
2
12
0
0
2417
23297 Female
4
14
0
0
5548
25529 Female
4
15
0
0
7859
29130 Male
2
16
8.5
7832
2786
30017 Male
4
14
0
17187 5301
30030 Female
1
15
0
3304
984
30180 Female
4
6
32
0
4776
32331 Female
1
18
16
3609
0
33628 Female
4
15
0
0
7067
36861 Male
16
0
7209
3666
37604 Female
1
19
0
4327
37973 Male
16
0
0
1354
38825 Female
1
13
14
5912
1051
40182 Female
1
16
0
0
1164
42197 Male
12
0
4130
1591
42487 Female
4
15
0
16763 3831
43861 Male
13
0
0
1384
3
11
0
0
2
4
2
1
1
1
44571 Female
1907
1208
3794
ID
Gender
Class
Hours
Work
Loans
1966
6264
7704
8548
8842
9274
12420
13641
14202
16603
16965
18543
21893
23297
25529
29130
30017
30030
30180
32331
33628
36861
37604
37973
38825
40182
42197
42487
43861
44571
Male
Male
Male
Female
Female
Female
Female
Male
Female
Female
Male
Female
Female
Female
Female
Male
Male
Female
Female
Female
Female
Male
Female
Male
Female
Female
Male
Female
Male
Female
2
2
3
3
1
1
1
2
2
4
4
3
2
4
4
2
4
1
4
1
4
2
1
1
1
1
1
4
1
3
18
17
12
14
15
9
17
14
12
10
15
9
12
14
15
16
14
15
6
18
15
16
19
16
13
16
12
15
13
11
0
16
0
0
0
27.5
16.5
0
0
23
16
24.5
0
0
0
8.5
0
0
32
16
0
0
0
0
14
0
0
0
0
0
0
8282
0
12355
5776
5029
0
0
0
15650
15725
0
0
0
0
7832
17187
3304
0
3609
0
7209
4327
0
5912
0
4130
16763
0
0
CC
Debt
2317
3168
2885
2104
981
1163
1080
2099
1907
2941
2998
2291
2417
5548
7859
2786
5301
984
4776
0
7067
3666
1208
1354
1051
1164
1591
3831
1384
3794

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