Universität Wien
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300131 VU Statistics course based on R (2023W)

5.00 ECTS (3.00 SWS), SPL 30 - Biologie
Continuous assessment of course work
ON-SITE
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. 60 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

First meeting (Vorbesprechung) on Monday 02.10.2023:
14:30 – 15:30 Seminar room 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5

Participation in the first meeting (Vorbesprechung) is obligatory (substitute possible), otherwise you will be de-registered from the course.

There are two parallel courses:
The first course will take place every Monday 14:30 - 16:45 Seminar room 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
The second course will take place every Tuesday 15:00 - 17:15 Semiar room 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
Each student is assigned to one of the two courses (see Moodle).

  • Monday 02.10. 14:30 - 15:30 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5 (Kickoff Class)
  • Monday 16.10. 14:30 - 16:45 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Tuesday 17.10. 15:00 - 17:15 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Monday 23.10. 14:30 - 16:45 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Tuesday 24.10. 15:00 - 17:15 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Monday 30.10. 14:30 - 16:45 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Tuesday 31.10. 15:00 - 17:15 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Monday 06.11. 14:30 - 16:45 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Tuesday 07.11. 15:00 - 17:15 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Monday 13.11. 14:30 - 16:45 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Tuesday 14.11. 15:00 - 17:15 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Monday 20.11. 14:30 - 16:45 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Tuesday 21.11. 15:00 - 17:15 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Monday 27.11. 14:30 - 16:45 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Tuesday 28.11. 15:00 - 17:15 Seminarraum 1.5, Biologie Djerassiplatz 1, 1.012, Ebene 1
  • Monday 04.12. 14:30 - 16:45 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Tuesday 05.12. 15:00 - 17:15 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Monday 11.12. 14:30 - 16:45 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Tuesday 12.12. 15:00 - 17:15 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Monday 08.01. 14:30 - 16:45 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Tuesday 09.01. 15:00 - 17:15 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Monday 15.01. 14:30 - 16:45 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Tuesday 16.01. 15:00 - 17:15 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Monday 22.01. 14:30 - 16:45 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Tuesday 23.01. 15:00 - 17:15 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Monday 29.01. 14:30 - 16:45 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5
  • Tuesday 30.01. 15:00 - 17:15 Seminarraum 5.1, Biologie Djerassiplatz 1, 5.131, Ebene 5

Information

Aims, contents and method of the course

Students are introduced to the free software environment R (https://www.r-project.org/) and how to perform statistical analyses using R. Each unit includes a theoretical and practical part: different statistical methods are first presented and should then be applied by the students to analyze provided datasets.

It is strongly recommended to bring a LAPTOP to the course, but working in groups of two using one laptop is also possible.

R is available for Windows, macOS, and Linux (for more information visit: https://www.r-project.org/).

Based on the learned methods and by gaining a general understanding for R, students should be able to perform their own statistical analyses for their master or PhD thesis, but also to further familiarize with R and other (statistical) methods.

Included topics: Statistical basics, installation of R and fundamentals, simple graphics, basic statistical tests (e.g., Shapiro-Wilk test, Levene’s test, t-test, U-test, ANOVA, Chi-squared test, correlations), power analysis, linear models (2-way ANOVA, multiple regression, ANCOVA, MANOVA), linear mixed models, generalized linear (mixed) model (e.g., for count, proportion, or binary data), multivariate statistics (e.g., principal component analysis), and further selected methods.

Assessment and permitted materials

Presence and participation in the units (obligatory), regular intermediate tests, final exam.
Continuous assessment of course work! (prüfungsimmanente Lehrveranstaltung)

Minimum requirements and assessment criteria

Presence and participation in the units (obligatory), regular intermediate tests, final exam.

Each part must be completed:
- Presence and participation in the units: max. 30 points
- 6 intermediate tests: max. 30 points (max. 5 points per test)
- Final exam: max. 40 points

89 – 100 points: Very good (1)
76 – 88 points: Good (2)
63 – 75 points: Satisfactory (3)
51 – 62 points: Adequate (4)
0 – 50 points: Unsatisfactory (5)

Examination topics

All statistical methods presented in the course.

Reading list

Relevant materials will be provided during the course.
For further information, several excellent books for R and online tutorials are available.
Examples for books:
- Statistics: An Introduction Using R. M. J. Crawley. Wiley.
- The R Book. M. J. Crawley. Wiley.
- R for Data Science. H. Wickham. O’Reilly.
- The Book of R. T. M. Davies. No Starch Press.

Association in the course directory

CoBeNe 2, MNB6, MZO4

Last modified: Mo 30.10.2023 13:48