# 401-6215-00L  Using R for Data Analysis and Graphics (Part I)

 Semester Autumn Semester 2021 Lecturers M. Mächler Periodicity yearly recurring course Language of instruction English

### Courses

NumberTitleHoursLecturers
401-6215-00 GUsing R for Data Analysis and Graphics (Part I)14s hrs
 Tue/1 14:15-16:00 CAB G 11 »
M. Mächler

### Catalogue data

 Abstract The course provides the first part an introduction to the statistical software R (Link) 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. We will make use of the graphical user interface RStudio: LinkNote: 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. Lecture notes An Introduction to R. Link Prerequisites / Notice The course resources will be provided via the Moodle web learning platform.As from FS 2019, subscribing via Mystudies should *automatically* make you a student participant of the Moodle course of this lecture,which is at Link

### Performance assessment

 Performance assessment information (valid until the course unit is held again) Performance assessment as a semester course ECTS credits 1.5 credits Examiners M. Mächler Type graded semester performance Language of examination English Repetition Repetition only possible after re-enrolling for the course unit. Online examination The examination may take place on the computer.

### Learning materials

 No public learning materials available. Only public learning materials are listed.

### Groups

 No information on groups available.

### Restrictions

 End of registration period Registration only possible until 14.10.2021

### Offered in

ProgrammeSectionType
Agricultural Sciences MasterData Science and Technolgy for Agricultural ScienceW+
Biology MasterElective Compulsory Master CoursesW
Biology MasterElective Compulsory Master CoursesW
Earth and Climate Sciences BachelorElectivesW
MAS in Sustainable Water ResourcesElective CoursesW
Statistics MasterStatistical and Mathematical Courses: not eligible for creditsE-
Environmental Sciences BachelorMethodes of Statistical Data AnalysisW