What is political science?
Political science deals with institutions, democracy, social structures, international relations, political philosophy and political content. Questions are answered, such as
- How democratic is a country? (democracy research)
- How does the party system of a specific country work and how can it be compared with other countries? (comparative political science)
- Does a political system achieve its goals? (performance research)
- How does the Swiss system work? (Swiss politics)
- Why was a vote adopted? (Swiss politics)
- Are there any just wars? (political philosophy)
- How do countries work together on climate protection and what kind of contracts do they have? (international relations)
- What impact do changes in a community have on neighboring communities? (policy analysis)
- How does the US and Swiss health care systems work? (policy analysis)
- How can elections be explained with supply and demand? (political economy)
- How can poverty be combated? (political economy of developing countries)
- How can a survey be designed that captures the population as accurately as possible? (methods)
- How can a large amount of data be processed in a way that suits the public? (political data journalism)
What are my specialties?
I deal with Swiss politics, political data journalism, quantitative methods and the statistical program R.
In Swiss politics, I am interested in topics such as elections and voting, participation and (the influence of) education. Data journalism is a very young discipline with great potential, especially in Germany. Everything that is current or new is interesting. In quantitative methods I deal with regression analyses and their interpretation, experiments and statistical learning.
This course gives an introduction into programming and computer science. The goal is to write better code in R and be able to share useful new functions with the whole R community. We start with the basic concepts (sequence, branch, loop) and learn when and how to write a function. We then see how we can write efficient and parallel code to make it faster. We look at a tool that helps us evaluate different code against each other to see which is faster. We then see how we can create in R Package and upload it to GitHub and CRAN. After that we will look at how to write a generic S3 function and object-oriented code together with the basic concept of it. At the end will spend some time with SQL and see how we can us it in R to read and write data from and to a MariaDB database.
The course provides an introduction to web development. First we take HTML, which is the basis of the web. We will then discuss how CSS can be used to layout the website and differentiate between mobile and desktop design. After this introduction, we will immerse ourselves in PHP and SQL to get an insight into backend programming. At the end of the seminar we will spend several weeks on front-end development and learn JavaScript. The focus will be on the JavaScript library D3 and we will learn how to create interactive graphics/maps.
Herbstsemester 2017: Advanced Statistical Models in Political Analysis using R (MA).
Syllabus
Link to the lecture
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In this course advanced methods are discussed and applied in R. It covers multilevel analysis, time series, panel regression and time series cross-sectional. See how to calculate a linear regression with matrix calculations and how to do maximum likelihood estimation. Both serve to provide a fundamental understanding of these two methods. During these two methods we will also look at how to package a function in R into a library.
This course teaches how to estimate models in R and how to interpret them in words and with graphics. The main focus of the course is logistic regression and ordinal logistic regression, how to calculate discrete changes and predicted probabilities and how to plot them. At the end of the course, we will discuss other models.