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FSS:SOC108 Data Analysis with SPSS - Course Information

## SOC108 Quantitative Data Analysis (with the use of SPSS)

**Faculty of Social Studies**

Autumn 2019

**Extent and Intensity**- 1/2/0. 6 credit(s). Type of Completion: zk (examination).
**Teacher(s)**- 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 **Timetable**- Wed 12:00–13:40 P31 Posluchárna A. I. Bláhy
- Timetable of Seminar Groups:

*P. Fučík*

SOC108/02: Thu 16:00–17:40 PC25,*M. Lakomý*

SOC108/03: Thu 18:00–19:40 PC25,*T. Doseděl* **Prerequisites**(in Czech)- ! NOW (
**SOCb1008**Data Analysis with SPSS ) && !**SOCb1008**Data Analysis with SPSS **Course Enrolment Limitations**- The course is only offered to the students of the study fields the course is directly associated with.

**fields of study / plans the course is directly associated with**- there are 20 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.
**Syllabus**- 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.

**Literature**- Mares, Rabušic, Soukup. 2015. Analýza sociálněvědních dat (nejen) v SPSS

*required literature*- FIELD, Andy P.
*Discovering statistics using SPSS : (and sex, drugs and rock 'n' roll)*. 2nd ed. London: Sage Publications, 2005. xxxiv, 779. ISBN 0761944524. 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

*recommended literature***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**- Czech
**Follow-Up Courses****Further comments (probably available only in Czech)**- The course is taught annually.
**Listed among pre-requisites of other courses**

- Enrolment Statistics (recent)

- Permalink: https://is.muni.cz/course/fss/autumn2019/SOC108