FSS:MEBn5033 Introduction to quanti - Course Information

MEBn5033 Introduction to quantitative data analysis

Extent and Intensity

1/1/0. 6 credit(s). Type of Completion: z (credit).

Teacher(s)

Mgr. Lukáš Lehotský, Ph.D. (lecturer)
doc. Mgr. Petr Ocelík, Ph.D. (lecturer)
Mgr. Colin Kimbrell, Ph.D. (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 14:00–15:40 M117

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: 0/20, 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

• Energy Security Studies (Eng.) (programme FSS, N-MS)
• Energy Policy Studies (programme FSS, N-EPS) (2)
• European Governance (programme FSS, N-EGO)
• European Politics (Eng.) (programme FSS, N-PL)
• European Studies (programme FSS, N-EVS) (2)
• European Studies (programme FSS, N-MS)
• European Governance (programme FSS, N-MS)
• International Relations and European Politics (programme FSS, N-IREP)
• Joint Master Programme in International Relations: Europe from the Visegrad Perspective (programme FSS, N-MS)
• International Relations and Energy Security (programme FSS, N-MS)
• International Relations and Energy Security (programme FSS, N-MVEB) (2)
• International Relations (programme FSS, N-MS)
• International Relations (programme FSS, N-MV) (2)

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

lectures, workshops, readings, assignments

Assessment methods

assignments grading

Language of instruction

English

Further Comments

Study Materials
The course is taught annually.

• Enrolment Statistics (Autumn 2020, recent)
  
• Permalink: https://is.muni.cz/course/fss/autumn2020/MEBn5033