SOC758 Statistical Data Analysis with SPSS

Faculty of Social Studies
Spring 2018
Extent and Intensity
1/1/0. 10 credit(s). Type of Completion: zk (examination).
Teacher(s)
Beatrice Elena Chromková Manea, M.A., Ph.D. (lecturer)
Supervisor
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
Prerequisites (in Czech)
SOUHLAS
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 18 student(s).
Current registration and enrolment status: enrolled: 0/18, only registered: 0/18
Fields of study the course is directly associated with
Course objectives
Statistical Data Analysis with SPSS is a course intended for students with few or no experience with the statistical software SPSS. The course is designed to introduce the basic statistics necessary to analyze data provided by various quantitative studies using SPSS. The course will offer students an overview of the following issues: 1) the basic notions in statistics - population, parameters, descriptive statistics, inferential statistics, sample, variables etc.; 2) creating data files in SPSS, 3) running statistical analysis, reading outputs and interpreting the results of the analysis. In other words, graduates of this course are able to:
- explain basic notions in statistics
- demonstrate ability to build databases in SPSS
- employ SPSS in order to analyse data
Syllabus
  • Seminar 1: Course management, introduction – strategies in statistical analysis: research problems and questions, measurement, variables
  • Seminar 2: Data display and databases. Working with databases - data files, entering data, merging files, syntax and output files – how to work with OPEN, SAVE, EDIT, VIEW, MERGE, UTILITIES in SPSS
  • Seminar 3: Variable transformation and selecting cases – how to work with TRANSFORM, RECODE, COMPUTE, COUNT, RANK CASES and SELECT CASES
  • Seminar 4: The basic of one-dimensional analysis – the distribution of categorical and continuous data – how to work with DESCRIPTIVE STATISTICS –FREQUENCIES, DESCRIPTIVES, EXPLORE, GRAPHS
  • Seminar 5: Normal distribution and normal standardized distribution.
  • Seminar 6: Testing hypotheses. Inference statistics
  • Seminar 7: Reading week
  • Seminar 8: Univariate analysis – testing hypothesis and comparing groups using means – how to work with MEANS, T-Test, ANOVA
  • Seminar 9: Basic bivariate analysis – conditional tables – how to work with CROSSTABS
  • Seminar 10 Statistical correlation and its measurement – correlation coefficients – how to work with CROSSTABS, CORRELATE – BIVARIATE
  • Seminar 11: How to detect the influence of a third variable – working with sub-samples and partial coefficients – how to work with CORRELATE – PARTIAL CORRELATION
  • Seminar 12: Factor analysis – how to work with DATA REDUCTION → FACTOR ANALYSIS, Basic linear regression – how to work with REGRESSION → LINEAR REGRESSION
  • Seminar 13: Review; Q&A
Literature
    required literature
  • Miller, R.L. - SPSS for Social Scientists, Houndsmill: Palgrave, 2002
  • FIELD, Andy P. Discovering statistics using SPSS : (and sex, drugs and rock 'n' roll). 3rd ed. Los Angeles: Sage, 2009. xxxiii, 82. ISBN 9781847879073. info
  • Handbook of data analysis. Edited by Melissa A. Hardy - Alan Bryman. London: Sage Publications, 2004. xvii, 704. ISBN 0761966528. info
  • DE VAUS, D. A. Analyzing social science data. First published. London: SAGE Publications, 2002. xxiv, 401. ISBN 0761959386. info
    recommended literature
  • Antonius, R. - Interpreting quantitative data with SPSS, London: Sage Publications, 2003
  • NORUŠIS, M. J. SPSS 15.0 advanced statistical procedures companion. Upper Saddle River, N.J.: Prentice Hall, 2007. xiv, 418. ISBN 9780132447126. info
Teaching methods
The course will be given in the form of workshops, where both teacher and students give oral presentations. Students will practice new techniques of data analysis in SPSS in the second part of the lecture. Questioning, explaining, collaborating, and demonstrating will be used as teaching methods and strategies. Students are expected to complete weekly readings prior to class, prepare their weekly assignments, and attend classes and seminars. There will be some homework during the semester. Homework (including Output) should submitted no later by Tuesday 10 a.m. Turn the electronic documents (as either a *.doc file or a *.pdf file) into the homework vault in is.muni.cz
Assessment methods
Conditions for passing the course:
1. Systematic work on and written responses to homework
2. Active participation and systematic work during the seminars
3. Final exam

Particular activities of students will be evaluated as follows:
30% - reading, responses and class participation
70% - final exam

The course ends with an exam based on the theoretical and practical issues presented during the semester: a written test (20 minutes) designed to evaluate the theoretical issues, and a practical test (max. 60-90 minutes - to be decided) aimed to evaluate SPSS usage in solving a statistical problem. 628 pages - reading
Language of instruction
English
Further Comments
The course is taught annually.
The course is taught: every week.
The course is also listed under the following terms Spring 2007, Spring 2009, Autumn 2010, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017.
  • Enrolment Statistics (Spring 2018, recent)
  • Permalink: https://is.muni.cz/course/fss/spring2018/SOC758

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