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Abstract
The course provides the second part an introduction to the statistical software R for scientists. Topics are data generation and selection, graphical functions, important statistical functions, types of objects, models, programming and writing functions.Note: This part builds on "Using R... (Part I)", but can be taken independently if the basics of R are already known.
Objective
The students will be able to use the software R efficiently for data analysis, graphics and simple programming
Content
The course provides the second part of an introduction to the statistical software R ( https://www.r-project.org/ ) for scientists. R is free software that contains a huge collection of functions with focus on statistics and graphics. If one wants to use R one has to learn the programming language R - on very rudimentary level. The course aims to facilitate this by providing a basic introduction to R. Part II of the course builds on part I and covers the following additional topics: - Elements of the R language: control structures (if, else, loops), lists, overview of R objects, attributes of R objects; - More on R functions; - Applying functions to elements of vectors, matrices and lists; - Object oriented programming with R: classes and methods; - Tayloring R: options - Extending basic R: packages The course focuses on practical work at the computer. We will make use of the graphical user interface RStudio: www.rstudio.org
Resources
Lecture Notes
All the slides (+ Quizes, Exercises & Solutions & R Demo scripts) are available from the Moodle page:https://moodle-app2.let.ethz.ch/course/view.php?id=26148and there also links to the Lam book and the R-project's own "Introduction to R"
General Information
- Language
- English
- Levels
- BSC , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
- Digital
- The exam takes place on devices provided by ETH Zurich.
Registration & Places
- Signup End
- 26.11.2026
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Using R for Data Analysis and Graphics (Part II) | No time listed | 14 h semesterly |
Offered In
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Statistics Master (The following courses belong to the curriculum of the Master's Programme in Statistics. The corresponding credits do not count as external credits even for course units where an enrolment at ETH Zurich is not possible.)