| Kurssprache | Turnus | Wochenstunden | ECTS | Prüfung |
|---|---|---|---|---|
| Englisch | WiSe | 2? | 2 | Klausur (60 Minuten) |
Inhalte
This course teaches basic skills in the use of the free software R. This provides a flexible and user-friendly programming environment and language, which is particularly suitable for statistical data analysis, the creation of scientific graphics and for simulations. The R software is now a widely used tool in many subject areas (New York Times article). In addition to teaching the R-specific syntax, the foundation is laid in particular for independent data analysis. Programming skills acquired in this course can also be helpful for learning other common programming environments, such as Python, Matlab, Gauss, Ox, Stata etc.
Outline
1. Installation, user interface
2. R basics and handling of data sets
3. Graphics and data visualisation
4. Flow control (loops etc.)
5. Statistical evaluation, regression analysis
6. Numerical optimisation
7. Efficient programming
8. Statistical simulations
9. Creating your own R packages
Literature
Kleiber, C. und Zeileis, A. (2004). Applied Econometrics with R. Springer.
Ligges, U. (2008). Programmieren mit R. Springer.
Additional literature
Vinod, H. (2008). Hands-on Intermediate Econometrics using R. World Scientific.
Everitt, B. (2005). An R and S-PLUS? Companion to Multivariate Analysis. Springer.
Chambers, J. M. (2008). Software for Data Analysis - Programming with R. Springer.
Target Group / Prerequisites
The course can be included as an elective course in both the Bachelor's and Master's degree programmes (2 ECTS) as well as in the IT training accompanying the degree programme (Studienbegleitende IT-Ausbildung (externer Link, ?ffnet neues Fenster)). Together with Programming in EViews (externer Link, ?ffnet neues Fenster) (Prof. Dr. Knoppik) and Introduction to Data Analysis with STATA (externer Link, ?ffnet neues Fenster) (Prof. Dr. Lea Cassar), the course is also part of a 3-course package (Programmieren für die Volkswirtschaftslehre) that can be added to the Bachelor's specialisation module Empirical Economic Research.
Alternatives to a certificate of achievement in Flexnow are a graded certificate (without the possibility of entry in FlexNow) or an ungraded certificate as proof of attendance in the course.
Prerequisite for participation in the course is basic econometric knowledge, such as that taught in Econometrics I, but no programming knowledge.
Grading
The overall grade of the course results from an exam on the computer. Passing the exam no worse than 4.0 is required to pass the course.