Syllabus
Introduction and motivation; (quantitative) research as seeking answers to the right questions (Tereza Plíštilová)
Research design, inference, and causalit
Data, data, data: measurement theory, measuring things, levels of measurement
Data, data, data in practice
Key descriptive statistics: measures of central tendency and measures of dispersion
Probability; standard normal distribution, binomial distribution (class on November 9 at 17:00, instead of 12:30).
Statistical inference and hypothesis testing
T-test (testing the difference between two groups) and experiments
Categorical and ordinal variables analysis: cross-tabs and chi-square; measures of association
Bivariate regression, principles, assumptions, and fit
Multiple regression
Model specification, interactions, and what's next
The troubleshooting tutorials are scheduled for: 19.10. at 17:00 in B229 16.11. at 17:00 in B216 (change of date from 15.11. to 16.11.) 14.12. at 16:00 in B229
Annotation
The purpose of this course is to introduce the students of international relations and security studies to political research methods, and specifically to their quantitative branch. Somewhat less formally, students will learn how to create or collect quantitative political data and how to use them to solve practical and/or theoretical political problems.
Quantitative data -- information about political phenomena captured and summarized in numbers -- is available literally on every corner, waiting just to be collected and analyzed. In this class, students get the chance to learn how to do it.
Being familiar with quantitative methods enables one to make policy decisions on the basis of a solid analysis of hard(er) empirical evidence, and to conduct systematic inquiry into the nature of international political and security phenomena. Last but not least, knowing quantitative methods enables one not be fooled by others when they try to support their arguments with lousy but seemingly sophisticated (because quantitative) analysis.
The class does not assume any prior knowledge of statistics or mathematics, essentially beyond elementary school. It does assume, however, a good deal of motivation on the part of students, as the learning curve may be somewhat steeper for some of the students.
The powerful (yet free) statistical package called R will be used in the class, in combination with the interface RStudio. Students are well advised to attend all classes and to keep up with the assigned readings as the material covered is highly cumulative.