Universität Wien
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300197 VU Introduction to R for Anthropologists (2022S)

3.00 ECTS (2.00 SWS), SPL 30 - Biologie
Continuous assessment of course work
REMOTE
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 24 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

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

Information

Aims, contents and method of the course

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.

Assessment and permitted materials

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.

Minimum requirements and assessment criteria

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.

Examination topics

Continuous assessment of the taught topics.

Reading list

- 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 )

Association in the course directory

BAN 5

Last modified: Th 11.05.2023 11:28