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401-6215-00L 1.5 Credits BSC , MSC D-USYS , D-BIOL , D-ERDW , D-PHYS
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Using R for Data Analysis and Graphics (Part I)

Lecturers & Examiners: Dr. Alain Hauser
VVZ CR n/a

Last Updated: 2026-06-01 11:30:27

Abstract

The course provides the first part an introduction to the statistical/graphical/data science software R (https://www.r-project.org/) for scientists. Topics covered are data generation and selection, graphical and basic statistical functions, creating simple functions, basic types of objects.

Objective

The students will be able to use the software R for simple data analysis and graphics.

Content

The course provides the first part of an introduction to the statistical software R 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 I of the course covers the following topics: - What is R? - R Basics: reading and writing data from/to files, creating vectors & matrices, selecting elements of dataframes, vectors and matrices, arithmetics; - Types of data: numeric, character, logical and categorical data, missing values; - Simple (statistical) functions: summary, mean, var, etc., simple statistical tests; - Writing simple functions; - Introduction to graphics: scatter-, boxplots and other high-level plotting functions, embellishing plots by title, axis labels, etc., adding elements (lines, points) to existing plots. The course focuses on practical work at the computer with R. We will make use of the graphical user interface RStudio IDE. Note: Part I of UsingR is complemented and extended by Part II, which is offered during the second part of the semester and which can be taken independently from Part I.

Resources

Lecture Notes

An Introduction to R.http://stat.ethz.ch/CRAN/doc/contrib/Lam-IntroductionToR_LHL.pdf

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
09.10.2025

Course Components

Type Title Time & Place Hours
lecture with exercise Using R for Data Analysis and Graphics (Part I)
  • Tue 14:15-16:00 (CAB G 11)
14 h semesterly

Offered In