PBM102 Analysis of Quantitative data

Faculty of Arts
Autumn 2022
Extent and Intensity
1/1/0. 4 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. PhDr. Petr Hlaďo, Ph.D. (lecturer)
doc. Mgr. Martin Sedláček, Ph.D. (lecturer)
Guaranteed by
doc. PhDr. Petr Hlaďo, Ph.D.
Department of Educational Sciences – Faculty of Arts
Contact Person: Mgr. Helena Juřicová
Supplier department: Department of Educational Sciences – Faculty of Arts
Timetable
Thu 10:00–11:40 B2.33
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 15 student(s).
Current registration and enrolment status: enrolled: 0/15, only registered: 0/15, only registered with preference (fields directly associated with the programme): 0/15
fields of study / plans the course is directly associated with
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
Study Materials
The course is taught each semester.
Teacher's information
https://elf.phil.muni.cz/elf3/course/view.php?id=362
The course is also listed under the following terms Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Autumn 2022, recent)
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