## MEBn5033 Introduction to quantitative data analysis

Faculty of Social Studies
Autumn 2021
Extent and Intensity
1/1/0. 6 credit(s). Type of Completion: z (credit).
Taught in person.
Teacher(s)
Mgr. Lukáš Lehotský, Ph.D. (lecturer)
Mgr. Petr Ocelík, Ph.D. (lecturer)
Mgr. Colin Kimbrell (assistant)
Guaranteed by
doc. PhDr. Břetislav Dančák, Ph.D.
Department of International Relations and European Studies - Faculty of Social Studies
Contact Person: Olga Cídlová, DiS.
Supplier department: Department of International Relations and European Studies - Faculty of Social Studies
Timetable
Wed 12:00–13:40 P24b
Prerequisites (in Czech)
! MEB433 Introduction to quanti && ! NOW ( MEB433 Introduction to quanti )
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 20 student(s).
Current registration and enrolment status: enrolled: 13/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 15 fields of study the course is directly associated with, display
Course objectives
The course introduces basics of quantitative data analysis to students. Each class consists of a lecture which introduces theoretical background and “mechanics” of a given concept or method and a workshop where students use this knowledge through practical tasks.
Learning outcomes
Upon successful completion of the course, students will be able to apply quantitative data analysis reasoning, specify appropriate techniques and rigorously use them. The emphasis will be put on the practical use of this knowledge.
Syllabus
• Organizational session / R modular architecture, data import
• Objects in R
• Data manipulation 1
• Data manipulation 2
• Introduction: why study statistics?
• Variable types and levels of measurement
• Descriptive statistics: measures of central tendency, position, and variability
• Frequency distributions and probability
• Contingency table and chi-squared test
• Measures of association: correlation coefficients
• Simple linear regression
• Data visualization
• Multiple linear regression
• Hypothesis testing
Literature
• FIELD, Andy P., Jeremy MILES and Zoë FIELD. Discovering statistics using R. First published. Los Angeles: Sage, 2012. xxxiv, 957. ISBN 9781446200452. info
• ADLER, Joseph. R in a nutshell. 2nd ed. Sebastopol, CA: O'Reilly, 2012. xix, 699. ISBN 9781449312084. info
• DALGAARD, Peter. Introductory statistics with R. 2nd ed. New York, N.Y.: Springer, 2008. xvi, 363. ISBN 9780387790534. info
Teaching methods