Universität Wien

300197 VU Introduction to R for Anthropologists (2020S)

3.00 ECTS (2.00 SWS), SPL 30 - Biologie
Continuous assessment of course work
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. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Wednesday 04.03. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 11.03. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 18.03. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 25.03. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 01.04. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 22.04. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 29.04. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 06.05. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 13.05. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 20.05. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 27.05. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 03.06. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 10.06. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 17.06. 09:00 - 11:00 EDV-Raum 2 Ökologie
Wednesday 24.06. 09:00 - 11:00 EDV-Raum 2 Ökologie

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. At the end of the course the student is expected to be able to use R to handle biological data and transform it into creative outputs.

Contents: The course 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: The course will be composed of 2 hour-long hybrid lectures per week, where the first hour should be focused on a theoretical presentation of the topic, and the second hour dedicated to a practical introduction to the covered topics. Students are then expected to gain further practical experience through independent work.

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 exam will take place during the last lecture 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 final exam to help them complete their tasks, such as web search or discussion with colleagues (the latter except during the final exam), special attention will be paid to plagiarism of other people’s code pieces.

Minimum requirements and assessment criteria

It is recommended for students taking this course to have a basic knowledge of Microsoft Excel, and be comfortable exploring new computer software.

Attendance, assignments and the final exam are weighted as 10%, 50% and 40%, respectively. A minimum final normalized score of 50% (rounded down to the closest integer) is required to complete the course.

Examination topics

Continuous assessment of the taught topics.

Reading list

Association in the course directory

BAN 5

Last modified: Sa 22.10.2022 00:29