ZURn4108 Descriptive Analysis of Quantitative Data

Faculty of Social Studies
Autumn 2022
Extent and Intensity
1/1/0. 4 credit(s). Type of Completion: z (credit).
Teacher(s)
Mgr. Klára Smejkal, Ph.D. (lecturer)
Mgr. Lucie Čejková (seminar tutor)
Mgr. Rostislav Zlámal (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
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. Work with Excel data: creating and modification of variables, import and export data.
  • 4. Working with data in SPSS: creating and modifying variables, importing and exporting data. 5. Univariate analysis: Data Cleaning. Distribution of categorical data and continuous data and their characteristics.
  • 6. Transformation and creation of variables, working with different types of variables.
  • 7. Exercise.
  • 8. Creating and Reporting of Descriptive Analyzes: tables and textual reports.
  • 9. Bivariation analysis and interpretation of data
  • 10. Creating and reporting descriptive analyzes: graphical outputs.
  • 10. Exercise (preparation for the final test).
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
The course is also listed under the following terms Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.
  • Enrolment Statistics (Autumn 2022, recent)
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