ZURn4108 Descriptive Analysis of Quantitative Data

Faculty of Social Studies
Spring 2023
Extent and Intensity
1/1/0. 4 credit(s). Type of Completion: z (credit).
Teacher(s)
Mgr. et Mgr. Karolína Bieliková (lecturer)
Mgr. Jana Blahošová (lecturer)
Mgr. Lucie Čejková (lecturer)
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 10:00–11:40 PC25
Prerequisites (in Czech)
TYP_STUDIA(MN)
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
  • Introduction: syllabus, completion of the course; objectives and content of the course
  • Quantitative research and empirical quantitative data
  • Basics of dealing with data in MS Excel
  • Basics of using IBM SPSS Statistics
  • Basics of univariate analysis
  • Transforming and creating variables, working with different types of variables
  • Sorting using contingency tables and data interpretation
  • Practice and repetition
  • Creating a report from descriptive data analysis and contingency tables: Charts, tables and text reports
  • Introduction to inferential statistics
Literature
    required 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
Teaching methods
lecture, seminar (SPSS exercises), reading
Assessment methods
• maximum two absences without prior excuse
• eight assignments
• final practical assignment
• final test
Language of instruction
Czech
Further Comments
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, Autumn 2022, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.
  • Enrolment Statistics (Spring 2023, recent)
  • Permalink: https://is.muni.cz/course/fss/spring2023/ZURn4108