PGBK120 Seminar on educational research: Analysis of Quantitative data

Faculty of Arts
Spring 2023
Extent and Intensity
12/0/0. 4 credit(s). Type of Completion: z (credit).
Taught partially online.
Teacher(s)
doc. Mgr. Martin Sedláček, Ph.D. (lecturer)
Guaranteed by
doc. Mgr. Martin Sedláček, Ph.D.
Department of Educational Sciences – Faculty of Arts
Contact Person: Mgr. Kateřina Zelená
Supplier department: Department of Educational Sciences – Faculty of Arts
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 25 student(s).
Current registration and enrolment status: enrolled: 0/25, only registered: 0/25
fields of study / plans the course is directly associated with
Course objectives
The aim of the course is to approach basics of statistical analyzing data acquired from a quantitative survey. Students will be introduced especially to work with statistical sets and variables. creating a set, data navigation and data cleaning, set operations, data translation, creating new variables, case selection and to basic data analysis methods.
Learning outcomes
Student will be able to:
- create a data matrix in SPSS (Statistica);
- clean and weight the data;
- understand an basic analyzes of descriptive statistics;
- apply these procedures to research problems;
- understand an analyzes of inductive statistics;
- critically assess research reports based on statistical data processing.
Syllabus
  • 1) Quantitative research – paradigm
  • 2) Data – measuring, data coding, matrix
  • 3) Basics of statistical analyzing data – potential and limitation 4) Descriptive statistics
  • 5) Frequency analysis
  • 6) Comparison of data allocation and average values of these allocations
  • 7) Basics of inferential statistics and testing of statistical hypothesis
  • 8) Finding relations between variables and evaluating strength of these relations – bivariational analysis using contingency tables, correlative analysis
Literature
    required literature
  • PUNCH, Keith. Úspěšný návrh výzkumu. Translated by Jan Hendl. Vydání druhé. Praha: Portál. 230 stran. ISBN 9788026209805. 2015. 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. 508 pp. ISBN 978-80-210-6362-4. 2015. Projekty Nakladatelství Munipress info
    recommended literature
  • BABBIE, Earl R. Adventures in social research : data analysis using IBM SPSS statistics. 8th ed. Los Angeles: Sage. xxiii, 456. ISBN 9781452205588. 2013. info
  • MUIJS, Daniel. Doing quantitative research in education with SPSS. 2nd ed. Los Angeles: SAGE. xv, 247. ISBN 9781849203241. 2011. info
    not specified
  • DISMAN, Miroslav. Jak se vyrábí sociologická znalost : příručka pro uživatele. 3. vyd. Praha: Karolinum. 374 s. ISBN 9788024601397. 2000. info
  • Úvod do metodologie psychologického výzkumu : jak zkoumat lidskou duši. Translated by Petr Bakalář, Illustrated by Ján Ferjenčík. Vyd. 2. Praha: Portál. 255 s. ISBN 9788073678159. 2010. URL info
Teaching methods
The course is taught as both lectures and seminars. Attendance and participation in the course (min. 75%).
Assessment methods
Written test.
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught: every week.
The course is also listed under the following terms Spring 2022.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/phil/spring2023/PGBK120