FSS:ZURn4108 Analysis of Quantitative Data - Course Information
ZURn4108 Descriptive Analysis of Quantitative Data
Faculty of Social StudiesAutumn 2023
- Extent and Intensity
- 1/1/0. 4 credit(s). Type of Completion: z (credit).
- Teacher(s)
- Mgr. Klára Smejkal, Ph.D. (lecturer)
Mgr. et Mgr. Michal Tkaczyk, Ph.D. (lecturer)
Mgr. et Mgr. Karolína Bieliková (seminar tutor)
Mgr. Jana Blahošová (seminar tutor)
Mgr. Lucie Čejková (seminar tutor) - Guaranteed by
- Mgr. et Mgr. Michal Tkaczyk, Ph.D.
Department of Media Studies and Journalism – Faculty of Social Studies
Contact Person: Mgr. Boris Rafailov, Ph.D.
Supplier department: Department of Media Studies and Journalism – Faculty of Social Studies - Timetable
- Fri 12:00–13:40 PC25
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Media industries and production (programme FSS, N-MSZU)
- Media Studies and Journalism (programme FSS, N-KS)
- Media Studies and Journalism (programme FSS, N-MSZU)
- Media research and analytics (programme FSS, N-MSZU)
- Course objectives
- The aim of the course is to acquaint students with the basics of quantitative data analysis of data used in media research using MS Excel and SPSS. It focuses mainly on basic data processing and data types, working with them, working with data files and variables (file creation, data entry and debugging, data export and import, file operations, data transformation, creation of new variables, selection of cases etc.) and methods of basic descriptive data analysis (descriptive statistics). At the same time, the course focuses on the reporting of descriptive analyzes and their interpretation.
- Learning outcomes
- Upon completion of the course, students will:
- be able to create a data matrix in Excel and SPSS, edit and transform data,
- be able to export and import data and data sets,
- have the knowledge of the basic methods of descriptive statistical data analysis,
- be able to use SPSS statistical software for descriptive data analysis. - Syllabus
- 1. Introduction to the course: objectives and content.
- 2. Logic of quantitative research, empirical quantitative data. Types of variables and their attributes.
- 3. Working with data in Excel: creating and editing variables, importing and exporting data.
- 4. Working with data in SPSS: creating and editing variables, importing and exporting data.
- 5. Basics of univariate analysis, data cleansing. Distribution of categorical data and continuous data and their characteristics.
- 6. Transformation and creation of variables, working with different types of variables.
- 7. Exercises.
- 8. Basics of crosstabs.
- 9. Crosstabs, graphs and data interpretation
- 10. Creating and reporting descriptive analyses: graphical outputs.
- 11. Exercises and practicing (preparing for the final test).
- 12. Basic insight into inferential statistics.
- Literature
- FIELD, Andy P. Discovering statistics using IBM SPSS statistics. 5th edition. Los Angeles: Sage, 2018, xxix, 1070. ISBN 9781526419521. info
- MAREŠ, Petr, Ladislav RABUŠIC and Petr SOUKUP. Analýza sociálněvědních dat (nejen) v SPSS (Data analysis in social sciences (using SPSS)). 1. vyd. Brno: Masarykova univerzita, 2015, 508 pp. ISBN 978-80-210-6362-4. Projekty Nakladatelství Munipress info
- BERKMAN, Elliot T. and Steven Paul REISE. A conceptual guide to statistics using SPSS. Los Angeles: Sage, 2012, xiii, 296. ISBN 9781412974066. info
- CLEGG, Frances. Simple statistics : a course book for the social sciences. Cambridge: Cambridge University Press, 1990, viii, 200. ISBN 0521288029. info
- Teaching methods
- lecture, seminar (SPSS practice exercise), reading
- Assessment methods
- practical tasks, final test
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught each semester. - Listed among pre-requisites of other courses
- Enrolment Statistics (Autumn 2023, recent)
- Permalink: https://is.muni.cz/course/fss/autumn2023/ZURn4108