1. How to use SPSS ? Aug, 17, 2011 Hirohide Yokokawa, M.D., Ph.D. Department of General Medicine, Juntendo University School of Medicine

2. The United States, Chicago, IL Since 1968 Merge with IBM at 2008, and generated to IBM SPSS Statistical Package for Social Science

3. http://www-01.ibm.com/software/analytics/spss/

4. 1.SPSS has an excellent potential to handle large scale data. 2.It is easy to conduct high technique analysis. 3.No need to enter long codes. (Clicking only) Strong Points of SPSS

5. 1. Set Excel Data up One Column is One variables One Row is One Case Caution ! Limited to Arabic numerals! Don’t enter any letters!

6. 2. Install Excel Data F O Data

7. 1 2 1.Select “ Excel”. 2.Chose your target file. 3.Open the file. 3

8. Install success !

9. 3. Check Errors and Distribution (Continuous Variables) 1 23

10. 1 2 3 1.Select variables 2.Click “Statistics”. 3.Select needed measurements.

11. Total number Check missing data Representative value

12. 4. Try to analyze (Basic analysis) 1.Categorical Data 1.Chi square Analysis 2.McNemar Test 2.Continuous Data 1.Two group comparison (Parametric/Nonparametric) 2.More than three group comparison 3.(Parametric/Nonparametric)

13. Categorical Variables Select Crosstabs 1 2 3

14. 1 3 1.Select variables 2.Click “Statistics”. 3.Click “Chi-square”. 2

15. 2 x 2 Table Total number Significance

16. 4-1-2. MacNemar Test 1

17. 4-2-1. Student t Test 1 2 3 4 5

18. Test for Equality of Variance If p value ≥0.05, accept p value of “Equal Variances” If p value <0.05, accept p value of “NOT Equal Variances”

19. 4-2-1. Paired t Test 1 2 3

20. 4-2-2. Mann Whitney Test 1 2 3 4

21. 4-2-2. ANOVA 1 2 3

22. 4-2-2. Kruskal Wallis Test 1 2 3 4

23. \ Click

24. 5. Try to analyze (Advanced analysis) 1.Correlation Analysis 2.Regression Analysis 1.Logistic regression analysis 2.Multiple regression analysis

25. 5-1. Correlation Analysis 1 2

26. \ Select appropriate Coefficient \ Enter two variables

27. \

28. 5-2. Multiple Regression Analysis

29. 1 2 3

30. 1 2 3

31. Β value P-value

32. 5-2. Logistic Regression Analysis 1 2 3

33. P-value Odds ratio