PSBB039 Data analysis

Faculty of Arts
Spring 2025
Extent and Intensity
1/1/0. 3 credit(s). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
doc. PhDr. Martin Jelínek, Ph.D. (lecturer)
Mgr. Helena Klimusová, Ph.D. (lecturer)
doc. PhDr. Petr Květon, Ph.D. (lecturer)
Guaranteed by
Mgr. Helena Klimusová, Ph.D.
Department of Psychology – Faculty of Arts
Contact Person: Jarmila Valchářová
Supplier department: Department of Psychology – Faculty of Arts
Prerequisites
Statistical Methods I, II; thesis assigned; the data collection has been finished or will have been finished during the semester.
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course follows the Statistical Methods I and II. The knowledge of these subjects is applied in the analysis of data from own projects. Specific issues of data analysis are consulted.
Learning outcomes
Students apply the knowledge base and the abilities acquired in the previous courses of statistics and methodology on data analysis of their own graduation research projects.
Syllabus
  • The aim of the course is to apply the knowledge base and the abilities acquired in the previous courses of statistics on students' own data of their graduation research projects. The course is based on individual consultations of data analysis of research projects. The statistical software, e.g. SPSS will be utilized.
Literature
    required literature
  • FIELD, Andy. Discovering Statistics Using IBM SPSS Statistics. 5th. Sage Publishing, 2017. ISBN 978-1-5264-4578-0. URL info
    recommended literature
  • HENDL, Jan. Přehled statistických metod : analýza a metaanalýza dat. Páté, rozšířené vydán. Praha: Portál, 2015, 734 stran. ISBN 9788026209812. info
Teaching methods
Students consult their procedures individually with their teachers, so the teaching takes place in block form on the basis of individual arrangements.
Assessment methods
To pass the colloquium, a student has to make a project of the data analysis and conduct the data analysis and the interpretation of the results.
Language of instruction
Czech
Further comments (probably available only in Czech)
The course is taught each semester.
The course is taught: in blocks.
The course is also listed under the following terms Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024.
  • Enrolment Statistics (Spring 2025, recent)
  • Permalink: https://is.muni.cz/course/phil/spring2025/PSBB039