Universität Wien

300197 VU Introduction to R for Anthropologists (2022S)

3.00 ECTS (2.00 SWS), SPL 30 - Biologie
Prüfungsimmanente Lehrveranstaltung
DIGITAL
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 24 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Donnerstag 03.03. 09:45 - 11:15 Digital
  • Donnerstag 10.03. 09:45 - 11:15 Digital
  • Donnerstag 17.03. 09:45 - 11:15 Digital
  • Donnerstag 24.03. 09:45 - 11:15 Digital
  • Donnerstag 31.03. 09:45 - 11:15 Digital
  • Donnerstag 07.04. 09:45 - 11:15 Digital
  • Donnerstag 28.04. 09:45 - 11:15 Digital
  • Donnerstag 05.05. 09:45 - 11:15 Digital
  • Donnerstag 12.05. 09:45 - 11:15 Digital
  • Donnerstag 19.05. 09:45 - 11:15 Digital
  • Donnerstag 02.06. 09:45 - 11:15 Digital
  • Donnerstag 09.06. 09:45 - 11:15 Digital
  • Donnerstag 23.06. 09:45 - 11:15 Digital
  • Donnerstag 30.06. 09:45 - 11:15 Digital

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Aims: The aim of this course is to introduce students to the programming language R used in various areas of biological anthropology, such as DNA analysis or geometric morphometrics, without the requirement of previous knowledge of programming languages. The student needs to be comfortable with text file handling and computer software in general. At the end of the course the student is expected to be able to use R to handle biological data and transform it into graphical outputs.

Contents: The course will be taught in English and will start with a general introduction to the R programming language and its relevance, followed by the topics of data manipulation, statistical analysis, data plotting, functions, optimization, and others. A non-binding list of topics to be presented is shown below:
- Variables and operators
- Data types
- Loops, statements and logic
- Functions and packages
- Input, output, and file management
- Data plotting and graphical output
- Statistic tests
- Speed and optimization

Method of the course: Video lectures will be uploaded on Monday mornings (no online presence required from part of the student). Part of a monthly assignment is given at the end of that lecture video, where the student must apply the taught knowledge in more thorough and creative pieces of code. The students must work on these assignment parts until Thursday, where from 9:45 to 11:15am there will be a weekly online troubleshooting session that the students must attend. Independent work and experimentation is therefore stimulated, which, as for any other spoken language, is a crucial part of the learning process for a programming language.

Art der Leistungskontrolle und erlaubte Hilfsmittel

After each lecture, part of a monthly assignment is given where the student must apply the taught knowledge in more thorough and creative pieces of code. A final assignment will take place during the last week of the semester, where the student will need to apply all knowledge acquired in the course to handle and interpret data, and produce graphical outputs. Since the students may bring or access any materials during the practical lectures and the assignments (including the final one) to help them complete their tasks, such as web search or discussion with colleagues, special attention will be paid to plagiarism of other people’s code pieces. The final assignment will heavily focus on customization of your own code and graphical outputs, in order for us to be able to better evaluate each student's capacities.

Mindestanforderungen und Beurteilungsmaßstab

This is a programming language module focused in R, therefore the students will need to be comfortable with computer software, file handling, and have a basic knowledge of Microsoft Excel. This is *extremely important*! Being part of BAN - Statistics, Mathematics and Computing in Anthropology, this module is most heavily focused on the "Computing" part, although with the application of some notions of statistics and mathematics. As this module will take place digitally, you are required to have access to a computer/laptop where you can install R and Rstudio (a tutorial on how to do so will be shown to you during the first lecture).

Therefore, please ensure that you fit these requirements before enrolling in the course, and that you are comfortable with basic computing.

The weekly assignments before the final one will weigh 55% of the final grade (combined), while the final assignment will account for the remaining 45%. A minimum final normalized score of 50% is required to complete the course.

Prüfungsstoff

Continuous assessment of the taught topics.

Literatur

- Nathaniel D. Phillips. YaRrr! The Pirate’s Guide to R, 2017 ( https://bookdown.org/ndphillips/YaRrr/YaRrr.pdf )
- W. N. Venables, D. M. Smith, R Core Team. An Introduction to R Notes on R: A Programming Environment for Data Analysis and Graphics Version 3.5.2, 2018 ( https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf )
- Trevor Martin. The Undergraduate Guide to R - A beginner‘s introduction to the R programming language ( http://www.biostat.jhsph.edu/~ajaffe/docs/undergradguidetoR.pdf )

Zuordnung im Vorlesungsverzeichnis

BAN 5

Letzte Änderung: Do 11.05.2023 11:28