VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.
Programming with R for Reproducible Research
Last Updated: 2026-06-01 11:33:51
Abstract
Deeper understanding of R: Function calls, rather than "commands".Reproducible research and data analysis via Sweave and Rmarkdown.Limits of floating point arithmetic.Understanding how functions work. Environments, packages, namespaces.Closures, i.e., Functions returning functions.Lists and [mc]lapply() for easy parallelization.Performance measurement and improvements.
Objective
Learn to understand R as a (very versatile and flexible) programming language and learn about some of its lower level functionalities which are needed to understand *why* R works the way it does.
Content
See "Skript": https://github.com/mmaechler/ProgRRR/tree/master/ETH
Resources
Lecture Notes
Material available from Githubhttps://github.com/mmaechler/ProgRRR/tree/master/ETH(typically will be updated during course)
Literature
Norman Matloff (2011) The Art of R Programming - A tour of statistical software design. no starch press, San Francisco. on stock at Polybuchhandlung (CHF 42.-). More material, notably H.Wickam's "Advanced R" : see my ProgRRR github page.
Learning Materials (Links)
- Main link
- Lecture webpage with all materials
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Programming with R for Reproducible Research |
|
14 h semesterly |
Offered In
-
Statistik Master (Die hier aufgelisteten Lehrveranstaltungen gehören zum Curriculum des Master-Studiengangs Statistik. Die entsprechenden KP gelten nicht als Mobilitäts-KP, auch wenn gewisse Lerneinheiten nicht an der ETH Zürich belegt werden können.)