Universität Wien

270191 VU Introduction to R (2024S)

3.00 ECTS (2.00 SWS), SPL 27 - Chemie
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. 15 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 06.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Thursday 07.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Wednesday 13.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Thursday 14.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Wednesday 20.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Thursday 21.03. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Wednesday 10.04. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Thursday 11.04. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Wednesday 17.04. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Thursday 18.04. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Wednesday 24.04. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Thursday 25.04. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Thursday 02.05. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Wednesday 08.05. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Wednesday 15.05. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock
  • Thursday 16.05. 17:00 - 18:30 Seminarraum 2 Währinger Straße 38 Dekanat 1. Stock

Information

Aims, contents and method of the course

In this course you will learn to code by using the statistical programming language R. We will cover typical (simple) cheminformatic analyses and model selected aspects of the current pandemic with R.

• Perform simple calculations
• 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

Assessment and permitted materials

Small scale project + oral evaluation + homework (bonus points).
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 laptops 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

BC-CHE II-8, CH-CBS-05, Synthese

Last modified: We 31.07.2024 12:06