SPSS Activities
14 A National Football League team is trying to draft the best players. Following the Combines Camp, the head coach and the chief assistant rank the top 15 players so they can compare their rankings prior to draft day. Table 14.28 presents their ranks.
Procedures and Questions A. Enter the data into SPSS and answer questions 1–3 on the facing page.
TABLE
14.28
Go to Analyze→Correlate→Bivariate n Put the head coach’s and the chief assistant’s ranks in the Variables window. n Check the boxes for Pearson and Spearman Correlation Coefficients. n Click OK. n
Data set.
PLAYER
HEAD COACH
CHIEF ASSISTANT
1
12.5
6
2
2.5
3.5
3
5
2
4
9
11
5
15
7
6
14
13
7
7
9
8
1
1
9
4
5
10
7
10
11
7
3.5
12
12.5
15
13
2.5
8
14
11
14
15
10
12
Q
1. What is the Pearson product-moment correlation coefficient between the two rankings? 2. What is the Spearman rank correlation coefficient () between the two coaches’ rankings? 3. Why are the correlations the same? 4. The team owner brings the coaches to her office and asks whom they should draft. Briefly describe the discussion that will take place in the owner’s office.
The middle school basketball coaches are excited that 60 girls signed up to try out for the three team levels (A, B, and C). Both coaches evaluated all of the girls with a six-item skills/drills activity. The coaches’ first cut was an attempt to pick 20 girls for the A team. After observing the girls’ tryouts, each coach listed their 20 girls. The results of their picks are listed in Table 14.29. Use SPSS to answer questions 5–14 on the next page. The coaches are interested in testing whether significant agreement exists in their picks at the .05 level.
Procedures and Questions A. Enter the data for the 60 girls into SPSS. The variable names are Coach 1
and Coach 2. Indicate whether each girl was picked (1) or not (0). There will be 28 (0,0), 12 (0,1), 12 (1,0), and 8 (1,1) entries. Use Analyze→Descriptive Statistics→Crosstabs. n Enter Coach 1 in the rows and enter Coach 2 in the columns. n Click on Statistics. n Check the boxes for (1) Chi-square, (2) Correlations, (3) Phi and Cramer’s V, and (4) Kappa. n Click Continue. n Click OK.
n
Data set.
COACH 2
COACH 1
No (not picked = 0)
Yes (picked = 1)
No (not picked = 0)
28
12
40
Yes (picked = 1)
12
8
20
40
20
60
TABLE
14.29
Q
5. Compare your 2 x 2 contingency table from SPSS with the one above. If it does not match, go back to your entered data and correct it. 6. What is the null hypothesis being tested in this example? 7. What are the degrees of freedom for this chi-square test? 8. What is the critical value for chi-square with this number of degrees of freedom? (See Appendix A.6). 9. What is the value of the calculated chi-square? 10. Is this statistically significant? 11. On what percentage of the players did the coaches agree? 12. What is the phi coefficient for their picks? 13. What is the kappa coefficient for their picks? 14. Describe the discussion that the coaches had following the first tryout.
A life coach is interested in the physical self-confidence that children gain as a result of participating in physical activities. The life coach wants to test the hypothesis that engagement in increasingly demanding physical activities results in increased physical self-confidence. He identifies 40 children as illustrated here: Those not in PE, intramurals, or school athletic activities Those in PE only (not intramurals or school athletic activities) Those in intramurals only (not PE or school athletic activities) Those in school athletic activities only
n = 10 n = 10 n = 10 n = 10
The life coach administers the Logan Kinley Physical Self-Confidence Inventory to all 40 children and ranks all of the scores from high (1 = most confident) to low (40 = least confident). The results are reflected in Table 14.30.
Procedures and Questions A. Enter the data into SPSS. There will be two variables (Activity Level and
Rank). For Activity Level, use the following codes: 1 = No PE, 2 = PE; 3 = Intramurals; and 4 = Athletics. Enter the ranks from above for each of the 40 children based on their activity level. Use Analyze→Nonparametric Tests→Legacy Dialogs→K Independent Samples. n Move Rank into the Test Variable List window. n Move Activity Level into the Grouping Variable window. n Highlight Activity Level by clicking on it. This will activate the Define Range button.
n
Data set.
NO PE
PE ONLY
INTRAMURALS
SCHOOL ATHLETICS
35
32
4
26
36
22
3
16
37
39
13
15
40
19
34
25
38
10
9
8
31
33
30
7
28
24
29
6
27
17
12
11
20
14
21
2
23
5
18
1
Enter the minimum range (1) and maximum range (4) for the grouping variable, and click Continue. n Check the Kruskal–Wallis H box under Test Type and click OK. n
Q 15. What is the life coach’s null hypothesis? 16. The alternative hypothesis is stated in the scenario. Which one do you test? 17. What are the mean ranks for the four activity levels? 18. What are the degrees of freedom associated with the test statistic? 19. Recall that the Kruskal–Wallis H statistic with large samples is distributed as a chi-square. What is the critical value for the Kruskal–Wallis test at = .05? See Appendix A.6. 20. What is your decision about the null hypothesis? 21. What does the life coach conclude?
TABLE
14.30
Procedures and Questions A. Enter the data into SPSS and answer questions 1–3 on the facing page.
TABLE
14.28
Go to Analyze→Correlate→Bivariate n Put the head coach’s and the chief assistant’s ranks in the Variables window. n Check the boxes for Pearson and Spearman Correlation Coefficients. n Click OK. n
Data set.
PLAYER
HEAD COACH
CHIEF ASSISTANT
1
12.5
6
2
2.5
3.5
3
5
2
4
9
11
5
15
7
6
14
13
7
7
9
8
1
1
9
4
5
10
7
10
11
7
3.5
12
12.5
15
13
2.5
8
14
11
14
15
10
12
Q
1. What is the Pearson product-moment correlation coefficient between the two rankings? 2. What is the Spearman rank correlation coefficient () between the two coaches’ rankings? 3. Why are the correlations the same? 4. The team owner brings the coaches to her office and asks whom they should draft. Briefly describe the discussion that will take place in the owner’s office.
The middle school basketball coaches are excited that 60 girls signed up to try out for the three team levels (A, B, and C). Both coaches evaluated all of the girls with a six-item skills/drills activity. The coaches’ first cut was an attempt to pick 20 girls for the A team. After observing the girls’ tryouts, each coach listed their 20 girls. The results of their picks are listed in Table 14.29. Use SPSS to answer questions 5–14 on the next page. The coaches are interested in testing whether significant agreement exists in their picks at the .05 level.
Procedures and Questions A. Enter the data for the 60 girls into SPSS. The variable names are Coach 1
and Coach 2. Indicate whether each girl was picked (1) or not (0). There will be 28 (0,0), 12 (0,1), 12 (1,0), and 8 (1,1) entries. Use Analyze→Descriptive Statistics→Crosstabs. n Enter Coach 1 in the rows and enter Coach 2 in the columns. n Click on Statistics. n Check the boxes for (1) Chi-square, (2) Correlations, (3) Phi and Cramer’s V, and (4) Kappa. n Click Continue. n Click OK.
n
Data set.
COACH 2
COACH 1
No (not picked = 0)
Yes (picked = 1)
No (not picked = 0)
28
12
40
Yes (picked = 1)
12
8
20
40
20
60
TABLE
14.29
Q
5. Compare your 2 x 2 contingency table from SPSS with the one above. If it does not match, go back to your entered data and correct it. 6. What is the null hypothesis being tested in this example? 7. What are the degrees of freedom for this chi-square test? 8. What is the critical value for chi-square with this number of degrees of freedom? (See Appendix A.6). 9. What is the value of the calculated chi-square? 10. Is this statistically significant? 11. On what percentage of the players did the coaches agree? 12. What is the phi coefficient for their picks? 13. What is the kappa coefficient for their picks? 14. Describe the discussion that the coaches had following the first tryout.
A life coach is interested in the physical self-confidence that children gain as a result of participating in physical activities. The life coach wants to test the hypothesis that engagement in increasingly demanding physical activities results in increased physical self-confidence. He identifies 40 children as illustrated here: Those not in PE, intramurals, or school athletic activities Those in PE only (not intramurals or school athletic activities) Those in intramurals only (not PE or school athletic activities) Those in school athletic activities only
n = 10 n = 10 n = 10 n = 10
The life coach administers the Logan Kinley Physical Self-Confidence Inventory to all 40 children and ranks all of the scores from high (1 = most confident) to low (40 = least confident). The results are reflected in Table 14.30.
Procedures and Questions A. Enter the data into SPSS. There will be two variables (Activity Level and
Rank). For Activity Level, use the following codes: 1 = No PE, 2 = PE; 3 = Intramurals; and 4 = Athletics. Enter the ranks from above for each of the 40 children based on their activity level. Use Analyze→Nonparametric Tests→Legacy Dialogs→K Independent Samples. n Move Rank into the Test Variable List window. n Move Activity Level into the Grouping Variable window. n Highlight Activity Level by clicking on it. This will activate the Define Range button.
n
Data set.
NO PE
PE ONLY
INTRAMURALS
SCHOOL ATHLETICS
35
32
4
26
36
22
3
16
37
39
13
15
40
19
34
25
38
10
9
8
31
33
30
7
28
24
29
6
27
17
12
11
20
14
21
2
23
5
18
1
Enter the minimum range (1) and maximum range (4) for the grouping variable, and click Continue. n Check the Kruskal–Wallis H box under Test Type and click OK. n
Q 15. What is the life coach’s null hypothesis? 16. The alternative hypothesis is stated in the scenario. Which one do you test? 17. What are the mean ranks for the four activity levels? 18. What are the degrees of freedom associated with the test statistic? 19. Recall that the Kruskal–Wallis H statistic with large samples is distributed as a chi-square. What is the critical value for the Kruskal–Wallis test at = .05? See Appendix A.6. 20. What is your decision about the null hypothesis? 21. What does the life coach conclude?
TABLE
14.30
