FF:PAM126 Analysis of Quantitive Data - Course Information
PAM126 Analysis of Quantitive Data
Faculty of ArtsSpring 2025
- Extent and Intensity
- 0/2/0. 6 credit(s). Type of Completion: z (credit).
In-person direct teaching - Teacher(s)
- Tomáš Lintner, Ph.D. (lecturer)
doc. Mgr. Martin Sedláček, Ph.D. (lecturer) - Guaranteed by
- doc. Mgr. Martin Sedláček, Ph.D.
Department of Educational Sciences – Faculty of Arts
Contact Person: doc. Mgr. Martin Sedláček, Ph.D.
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 5 student(s).
Current registration and enrolment status: enrolled: 0/5, only registered: 0/5 - fields of study / plans the course is directly associated with
- Andragogy (programme FF, N-ANDR_) (2)
- Course objectives
- The aim of the course is to approach the methods of statistical analyzing data acquired from a quantitative survey. Students will be introduced especially to work with statistical sets and variables, statistical hypothesis testing and the basics of making multilevel models.
- Learning outcomes
- After finishing the course, students are able to:
- to create a set, data navigation and data cleaning, set operations, data translation, creating new variables, case selection and to basic data analysis methods;
- decompose of categorical and continuous data and characteristics of this decomposition - univariational analysis;
- compare of data allocation and average values of these allocations: t-test, variants analysis;
- apply of basics of inferential statistics and testing of statistical hypothesis;
- find the relations between variables and evaluating strength of these relations – bivariational analysis using contingency tables, correlative analysis;
- understand the linear relations between continuous variables: linear;
- understand the data reduction using factor analysis as an attempt to identify factors explaining higher correlation between particular variables (basics of multivariational analysis);
- critically assess research reports based on statistical data processing. - Syllabus
- (1) decomposition of categorical and continuous data and characteristics of this decomposition - univariational analysis;
- (2) comparison of data allocation and average values of these allocations: t-test, variants analysis;
- (3) basics of inferential statistics and testing of statistical hypothesis;
- (4) finding relations between variables and evaluating strength of these relations – bivariational analysis using contingency tables, correlative analysis;
- (5) finding linear relations between continuous variables: linear regression and scatterplot;
- (6) data reduction using factor analysis as an attempt to identify factors explaining higher correlation between particular variables (basics of multivariational analysis)
- Literature
- required literature
- SOUKUP, Petr and Ladislav RABUŠIC. Několik poznámek k jedné obsesi českých sociálních věd, statistické významnosti (Some Notes on the Obsession of the Czech Social Sciences with Statistical Significance). Sociologický časopis/ Czech Sociological Review. Praha: Sociologický ústav AV ČR, 2007, vol. 43, No 2, p. 379-395. ISSN 0038-0288. info
- MUIJS, Daniel. Doing quantitative research in education with SPSS. 2nd ed. Los Angeles: SAGE, 2011, xv, 247. ISBN 9781849203241. info
- recommended literature
- RABUŠIC, Ladislav and Marie TRAXLEROVÁ. Jak měřit bezmocnost (On measuring powerlessness). Data a výzkum. Praha: Sociologický ústav ČAV, 2008, vol. 2, No 1, p. 7-29. ISSN 1802-8152. info
- ANDĚL, J. Základy matematické statistiky. Praha: MFF UK, 2005. info
- not specified
- HENDL, Jan. Přehled statistických metod zpracování dat :analýza a metaanalýza dat. Vyd. 1. Praha: Portál, 2004, 583 s. ISBN 8071788201. info
- FIELD, Andy. Discovering Statistics Using IBM SPSS Statistics. 5th. Sage Publishing, 2017. ISBN 978-1-5264-4578-0. URL info
- MAREŠ, Petr, Ladislav RABUŠIC and Petr SOUKUP. Analýza sociálněvědních dat (nejen) v SPSS (Data analysis in social sciences (using SPSS)). První. Brno: Masarykova univerzita, 2015, 508 pp. ISBN 978-80-210-6362-4. info
- BABBIE, Earl R. Adventures in social research : data analysis using IBM SPSS statistics. 8th ed. Los Angeles: Sage, 2013, xxiii, 456. ISBN 9781452205588. 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. - Teacher's information
- https://elf.phil.muni.cz/elf3/course/view.php?id=362
- Enrolment Statistics (Spring 2025, recent)
- Permalink: https://is.muni.cz/course/phil/spring2025/PAM126