FF:PAM126 Analysis of Quantitive Data - Course Information
PAM126 Analysis of Quantitive Data
Faculty of ArtsAutumn 2020
- Extent and Intensity
- 0/2/0. 6 credit(s). Type of Completion: z (credit).
- 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: doc. Mgr. Martin Sedláček, Ph.D.
Supplier department: Department of Educational Sciences – Faculty of Arts - Timetable
- Tue 8:00–9:40 B2.33
- 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
- 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
- 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, 2015, 508 pp. ISBN 978-80-210-6362-4. Projekty Nakladatelství Munipress 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
- MUIJS, Daniel. Doing quantitative research in education with SPSS. 2nd ed. Los Angeles: SAGE, 2011, xv, 247. ISBN 9781849203241. info
- not specified
- PALLANT, Julie. SPSS survival manual : a step by step guide to data analysis using IBM SPSS. 7th edition. London: McGraw Hill, Open university press, 2020, xvi, 361. ISBN 9780335249497. info
- Data analysis using SPSS for Windows, version 8 to 10a beginner's guide. Edited by Jeremy J. Foster. London: Sage Publications, 2001, xvii, 252. ISBN 0761969268. info
- ŘEZANKOVÁ, Hana. Analýza kategoriálních dat pomocí SPSS. Vyd. 1. Praha: Vysoká škola ekonomická, 1997, 78 s. ISBN 8070797282. 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.
- Enrolment Statistics (Autumn 2020, recent)
- Permalink: https://is.muni.cz/course/phil/autumn2020/PAM126