1. Statistics in SPSS Lecture 1
Petr Soukup, Charles University in Prague

2. Basic Info 2

3. Info Teacher: Petr Soukup (Dep. of Sociology)
Consultation hour : Tue, , Jinonice, 3065
Student’s introduction

4. Info
Syllabus : see SIS (code JSM406)
Literature:
Field, A. (2000). Discovering statistics using SPSS for Windows :advanced techniques for the beginner. London : Sage. 2006, 2009 editions (2nd or 3rd)
Norušis,M., J. (2005).SPSS 13.0 :statistical procedures companion. New Jersey: Prentice Hall.
Czech students: Mareš, Rabušic, Soukup. Analýza sociálněvědních dat (nejen) v SPSS muniPRESS, Brno. (ch. 2 – ch. 10) 4

5. Requirements
Grading will be based on homework assignments (8 mandatory assignments, each worth 5 points) and a final in-class exam (worth 60 points). Students may earn up to 100 total points.
Final grades:
points = grade A
points = grade B
points = grade C
points = grade D
points = grade E
< 50 points = not passed
Note: It is expected that student is familiar with social science reseach (read some text about it or passed some course) 5

6. Main goal Introduction to social science statistics
Introduction to SPSS environment
Final: Students are able to analyze social science data for their purpose (e.g. preparation of thesis)
More topics can be found in Advanced courses (IES and ISS at the Faculty) 6

7. Intro to statistics 7

8. Statistics Different meaning of the the expression
Is it important? Why?
Is it difficult ? Why?
Is it boring? 8

9. Basic branches of statistics
Descriptive stats
Probability*
Mathematical stats (Statistical inference)
* nearly absent in the course (nice and small book: John Haigh: Probability – A very short Introduction, Oxford, 2012) 9

10. Special branches of statistics
Sampling theory
Time Series Analysis
and many others 10

11. Intro to descriptive stats11

12. Basic concepts Variable Opposite of variable? Examples of variables?12

13. Types of variables (different measurements)
Nominal (NOMEN)
Ordinal (ORDO)
Cardinal (scale)
Examples, discussion about coding schemes 13

14. Descriptive stats I Why we use descriptive stats?
Different tools for individual types of variables 14

15. Descriptive stats II Central tendency (What is typical value?)
Dispersion/Variance (Are there many differencies or not?)
Distribution (Skewness and Kurtosis) – Is the distribution of values symmetric and with high peak or assymeric and flat?
Pictures and examples 15

16. Central tendency Mode - nominal Median - ordinal
Mean (Average) – cardinal
Logic of statistical procedures according to type of variables
Graphical presentation of mean and median (why mean is used so often?) 16

17. Review of statistical SW17

18. Statistical software What is statistical SW? General vs. Specialized
Other tools for stats 18

19. General statistical software
IBM SPSS Statistics (v. 25)
Stata (v. 15) for universities, possibility to add do files
SAS (v. 10) not only for stat, for professionals
Statistica (v. 13) – very nice graphics
R-project – the best and free ( ) 19

20. Specialized statistical software
usually for one procedure or for the family of close approaches
E.g. AMOS from IBM for structural equation modelling ( 20

21. Other tools for stat Mainly spreadsheets can do quite a lot from stats
Excel – functions, Data analysis tool and many add-ins (free and commercial as well)
Calc (from Open Office) – only functions (the same as in MS Excel)
All stats in JSM406 can be computed via Excel or Calc (only outputs would not be so friendly and nice) 21

22. HW 22

23. HW1
Try to describe three variables of different types, i.e. one nominal, one ordinal and one cardinal (scale)
For nominal and ordinal variables define possible values (answers) 23

24. Thanks for your attention24