ESOn4010 Statistical Data Analysis with SPSS

Faculty of Social Studies
Spring 2023
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)
Guaranteed by
Beatrice Elena Chromková Manea, M.A., Ph.D.
Department of Sociology – Faculty of Social Studies
Contact Person: Ing. Soňa Enenkelová
Supplier department: Department of Sociology – Faculty of Social Studies
Timetable
Tue 8:00–9:40 PC25
Prerequisites (in Czech)
! SOC758 Statistical Data Analysis
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 25 student(s).
Current registration and enrolment status: enrolled: 2/25, only registered: 0/25, only registered with preference (fields directly associated with the programme): 0/25
fields of study / plans 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 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.
Learning outcomes
Students will be able to:
- explain basic notions in statistics
- demonstrate ability to build databases in SPSS
- employ basic 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: Basic bivariate analysis – conditional tables – how to work with CROSSTABS
  • Seminar 7: Reading week
  • Seminar 8: Inference statistics. Chi-square test.
  • Seminar 9: Testing hypothesis and comparing groups using means – how to work with MEANS, T-Test, ANOVA
  • Seminar 10: Statistical correlation and its measurement – correlation coefficients – how to work with CROSSTABS, CORRELATE – BIVARIATE
  • Seminar 11: Factor analysis – how to work with DATA REDUCTION → FACTOR ANALYSIS
  • Seminar 12: Basic linear regression – how to work with REGRESSION → LINEAR REGRESSION
  • Seminar 13: Review; Q&A
Literature
    required literature
  • 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
  • DE VAUS, D. A. Analyzing social science data. First published. London: SAGE Publications, 2002, xxiv, 401. ISBN 0761959386. info
    recommended literature
  • Miller, R.L. - SPSS for Social Scientists, Houndsmill: Palgrave, 2002
  • Antonius, R. - Interpreting quantitative data with SPSS, London: Sage Publications, 2003
  • Handbook of data analysis. Edited by Melissa A. Hardy - Alan Bryman. London: Sage Publications, 2004, xvii, 704. ISBN 0761966528. info
Teaching methods
The course will be given in the form of workshops. Students will practice new data analysis techniques in SPSS in the second part of the lecture. Questioning, explaining, collaborating, and demonstrating will be used as teaching methods and strategies. Students must complete weekly readings before class, prepare their weekly assignments, and attend classes and seminars. There will be some homework during the semester. Homework (including Output) should be submitted no later by Sunday 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 and written responses to homework
2. Active participation and systematic work during the seminars
3. Final test

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

The course ends with a test based on the theoretical and practical issues presented during the semester: a written part (20 minutes) designed to evaluate the theoretical issues and a practical one (max. 90 minutes) to evaluate SPSS usage in solving a statistical problem.
Language of instruction
English
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
General note: The course is designed for students with none or little experience in analyzing social data with SPSS.
Information on course enrolment limitations: The course is designed for students with none or little experience in analyzing social data with SPSS.
Teacher's information
Dr. Beatrice Chromková Manea manea@fss.muni.cz, Room 3.57 Office Hours: online by appointment
The course is also listed under the following terms Spring 2020, Spring 2021, Spring 2022, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2023, recent)
  • Permalink: https://is.muni.cz/course/fss/spring2023/ESOn4010