PSMB003 Data analysis

Faculty of Arts
Spring 2019
Extent and Intensity
1/1/0. 3 credit(s). Type of Completion: k (colloquium).
Teacher(s)
doc. PhDr. Martin Jelínek, Ph.D. (lecturer)
Mgr. Helena Klimusová, 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 knowledge base of the Statistical methods I and II will be reviewed in the introductory seminars. Students will present their research projects and data analysis projects. Analysis of the students' own data will be main part of the course. The statistical software, e.g. SPSS will be utilized.
Literature
    recommended literature
  • Bartholomew, D., Steele, F., Galbraith, J., Moustaki, I. (2011). Analysis of Multivariate Social Science Data. New York: Chapman and Hall/CRC.
  • FIELD, Andy P. Discovering statistics using IBM SPSS statistics. 5th edition. Los Angeles: Sage, 2018, xxix, 1070. ISBN 9781526419521. info
  • 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 practices individually with lecturers according to the data analytical approach used. During consecutive consultations the details of the statistical analyses are elaborated.
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)
Study Materials
The course is taught each semester.
The course is taught: in blocks.
Teacher's information
The course is offered annually in both semesters, autumn and spring. It is advisable to enroll in the course only in the semester, when the student has the data collection for the diploma thesis either already completed or in the final phase.
The course is also listed under the following terms Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Autumn 2024, Spring 2025.
  • Enrolment Statistics (Spring 2019, recent)
  • Permalink: https://is.muni.cz/course/phil/spring2019/PSMB003