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

5.00 ECTS (3.00 SWS), SPL 30 - Biologie
Prüfungsimmanente Lehrveranstaltung
VOR-ORT
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 60 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

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).

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

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

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.

Art der Leistungskontrolle und erlaubte Hilfsmittel

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

Mindestanforderungen und Beurteilungsmaßstab

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)

Prüfungsstoff

All statistical methods presented in the course.

Literatur

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.

Zuordnung im Vorlesungsverzeichnis

CoBeNe 2, MNB6, MZO4

Letzte Änderung: Mo 30.10.2023 13:48