Universität Wien

300232 VU Introduction to coding in R (VU): A hands-on approach (2023S)

study design

5.00 ECTS (3.00 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

Obligatory introductory meeting: 7.3.2023; 10.00 am (link will be sent out to all accepted students and top 3 on the waiting list)

Structure of the course:
The course will have two components
(i) an online lecture available as videos on moodle (can be watch at any time), which will be complemented by three online plenum discussions to the lecture content in May (see below)
(ii) a blocked in-person course in the beginning of July (every day from 09.00-17.00; dates: 10th to 14th of July)

Online plenum discussions will take place on: 4th , 11th and 25th of May, always 17.00. Please always use the same zoom link to log in on all three days:

Alfred Burian is inviting you to a scheduled Zoom meeting.

Topic: Plenum - hands on R course
Time: May 4, 2023 05:00 PM Amsterdam, Berlin, Rome, Stockholm, Vienna

Join Zoom Meeting
https://ufz-de.zoom.us/j/9292738517?pwd=M2sySUtuTFJaYjUvSFArTk1RMWNuQT09

Meeting ID: 929 273 8517
Passcode: 755024

  • Monday 10.07. 09:00 - 17:00 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Tuesday 11.07. 09:00 - 17:00 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Wednesday 12.07. 09:00 - 17:00 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Thursday 13.07. 09:00 - 17:00 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Friday 14.07. 09:00 - 17:00 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1

Information

Aims, contents and method of the course

The aim of this course is to gain hands-on experience in the statistical software R. You will need no prior knowledge in R, an introduction to all basic terms and operations will be provided. However, participating students should have a basic understanding of statistics - we will focus on how to implement things and we will not cover mathematical background information.

Specific targets of the course are (i) data management, (ii) data summary and transformations, (iii) most common statistical operations (focus on t-tests, ANOVA and regressions) and (iv) data visualization in R.

Overall, the most important learning goal of the course is to gain confidence and experience in data analyses and to put you in a good position to design sampling and analyze data for degree projects.

Assessment and permitted materials

Exam (40%), active participation (20%), submission of one work example (40%).

Minimum requirements and assessment criteria

50% of total achievable points most be reached in all three categories mentioned above.

Sehr gut 89-100%
Gut 76-88%
Befriedigend 63-75%
Genügend 50-62%
Nicht Genügend < 50%

Examination topics

Content of the 15 lectures - no coding is required for the written exam.

Reading list

Association in the course directory

MEC-5, MNB2, MBO 7, MZO W-9, MZO W3, MAN 3, M-WZB

Last modified: Tu 14.03.2023 12:09