Warning! The directory is not yet complete and will be amended until the beginning of the term.
270147 VU Introduction to R (2022S)
Continuous assessment of course work
Labels
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).
- Registration is open from Tu 01.02.2022 08:00 to Th 24.02.2022 23:59
- Deregistration possible until Th 24.02.2022 23:59
Details
max. 15 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
In person, Wednesday and Thursday, 5-6.30pm
- Wednesday 02.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 03.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Wednesday 09.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 10.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Wednesday 16.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 17.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Wednesday 23.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 24.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Wednesday 30.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 31.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Wednesday 06.04. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 07.04. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Wednesday 27.04. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 28.04. 17:00 - 18:30 Seminarraum 3 Organische Chemie 1OG Boltzmanngasse 1
- Wednesday 04.05. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 05.05. 17:00 - 18:30 Seminarraum 3 Organische Chemie 1OG Boltzmanngasse 1
- Wednesday 11.05. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 12.05. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Wednesday 18.05. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 19.05. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Wednesday 25.05. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Wednesday 01.06. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 02.06. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Wednesday 08.06. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 09.06. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Wednesday 15.06. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Wednesday 22.06. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 23.06. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Wednesday 29.06. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
- Thursday 30.06. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
Information
Aims, contents and method of the course
Assessment and permitted materials
Small scale project + oral evaluation + homework (bonus points)
All materials are allowed during the exam. Group work is not allowed.
All materials are allowed during the exam. Group work is not allowed.
Minimum requirements and assessment criteria
There are no prerequisites for this course. Participants are expected to bring their own laptop to class.Final assessment is based on working R implementation of the small scale project + positive oral evaluation. Homework is not mandatory but earns bonus points if correct; homework is submitted within one week after first announcement
Examination topics
Reading list
Association in the course directory
AN-2
Last modified: Th 03.03.2022 16:09
• Make simple plots
• Perform multiple operations in sequence, or at once
• Troubleshoot errors
• Exploratory data analysis
• Data wrangling
• Find help for functions
• Basic data modeling and interpretation of results
• Identify problems with your code/analysis (critical self-analysis)
• Format “clean” data and clean up “dirty” data