SOCb1008 Quantitative Data Analysis (with the use of SPSS)

Faculty of Social Studies
Autumn 2021
Extent and Intensity
1/2/0. 6 credit(s). Type of Completion: zk (examination).
Taught in person.
prof. PhDr. Ladislav Rabušic, CSc. (lecturer)
Mgr. Petr Fučík, PhD. (seminar tutor)
Mgr. Ing. Tomáš Doseděl, Ph.D. (seminar tutor)
Mgr. Martin Lakomý, Ph.D. (seminar tutor)
Guaranteed by
prof. PhDr. Ladislav Rabušic, CSc.
Department of Sociology - Faculty of Social Studies
Contact Person: Ing. Soňa Enenkelová
Supplier department: Department of Sociology - Faculty of Social Studies
Wed 12:00–13:40 P52
  • Timetable of Seminar Groups:
SOCb1008/01: Tue 8:00–9:40 PC25, M. Lakomý
SOCb1008/02: Tue 14:00–15:40 PC25, T. Doseděl
SOCb1008/03: Tue 18:00–19:40 PC25, P. Fučík
! SOC108 Data Analysis with SPSS &&( SOCb1006 Methodology of Social Sciences || SOC106 Methodology of Social Sciences )
It is essential to register this course in ther 3rd semesetr after completion the course SOCb1006.
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.

The capacity limit for the course is 60 student(s).
Current registration and enrolment status: enrolled: 57/60, only registered: 0/60
fields of study / plans the course is directly associated with
there are 8 fields of study the course is directly associated with, display
Course objectives
This course is aimed undergraduate students (bachelor’s programme) at Faculty of Social Study. General objective of the course is to introduce students in knowledge of basic concepts of statistics and the ability to analyse quantitative survey data using special statistical software SPSS (Statistical Packet for Social Sciences). During the course, students will learn how to record survey data, clean the data and transform the data. They will master procedures of descriptive analysis (perform computations): univariate analysis; comparison of means; t-test; analysis of variance; inferential statistics and hypothesis testing; bivariate analysis - crosstabulation and measurement of the strength of association/correlation between two variables; elaboration and partial correlation; regression analysis; factor analysis. At the end of the course student should be able to understand basic statistical concepts and models and understand and perform statistical analysis of surveys’ data – to assess and apply particular statistical techniques in SPSS, which are relevant to research questions. He/she is also able to reflex of all process surveys’ data preparation and analysis in the critical way.
Learning outcomes
Students obtain knowledge of basic concepts of statistics and the ability to analyse quantitative survey data.
  • 1. Basic strategies of quantitative research: research questions, operationalisation, variables;
  • 2. How to prepare data for the analysis using SPSS -(module files; edit, view, utilities)
  • 3. Distribution of categorical data and univariate analysis (module descriptive statistics - frequencies, explore);
  • 4. Distribution of interval data and their analysis;
  • 5. Transformation of data (module transform, recode, compute, count, rank cases);
  • 6. Normal Distribution and hypothesis testing - statistical inference;
  • 7. Comparison of means: t-test, one-sample t-test; independent-samples t-test); analysis of variance;
  • 8. Bivariate analysis - crosstabulation;
  • 9. Strength of association - coefficients of association and correlation;
  • 10. Spurious correlations, elaboration, partial correlation;
  • 11. Linear regression;
  • 12. Factor analysis.
    required literature
  • RABUŠIC, Ladislav, Petr SOUKUP and Petr MAREŠ. Statistická analýza sociálněvědních dat (prostřednictvím SPSS) (Statistical data analysis (with SPSS)). 2. přepracované vyd. Brno: Masarykova univerzita, 2019. 573 pp. ISBN 978-80-210-9247-1. URL info
    recommended literature
  • FIELD, Andy P. Discovering statistics using IBM SPSS statistics. 5th edition. Los Angeles: Sage, 2018. xxix, 1070. ISBN 9781526419521. info
  • NORUŠIS, M. J. SPSS introductory statistics : student guide. Chicago: SPSS, 1990. 420 s. ISBN 013178062X. info
  • PALLANT, Julie. SPSS survival manual :a step by step guide to data analysis using SPSS for Windows (version 10 and 11). 1st pub. Buckingham: Open University Press, 2001. xvi, 286 s. ISBN 0-335-20890-8. info
  • BRYMAN, Alan and Duncan CRAMER. Quantitative data analysis with SPSS release 8 for Windows : a guide for social scientists. 1st ed. London: Routledge, 1999. xiv, 303. ISBN 0415206960. info
  • SPSS Base 14.0 : user's guide. Chicago: SPSS Inc., 2005. xxv, 738. ISBN 0132218046. info
Teaching methods
Lecture (demonstration of basic statistical concepts, models, and techniques), exercises in computer rooms (demonstration of computing examples in SPSS), weekly assigned homeworks (self-computing tasks).
Assessment methods
Exam: written test consisting of 2 parts: in the first one, students will be asked to explain basic statistical concepts and/or procedures of statistical analysis. In the second one, they will have to solve three statistical tasks - computation by using SPSS.
Language of instruction
Follow-Up Courses
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
General note: Předmět si zapisují studující dřívějších imatrikulačních ročníků, než 2021/22.
Information on course enrolment limitations: Předmět si zapisují studující dřívějších imatrikulačních ročníků, než 2021/22
The course is also listed under the following terms Autumn 2019, Autumn 2020.
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