Universität Wien

330175 VU Multivariate Analyses Methods and their applications in Nutritional Sciences (2024W)

7.00 ECTS (4.00 SWS), SPL 33 - Ernährungswissenschaften
Continuous assessment of course work
REMOTE

Summary

1 Stüger , Moodle
Fr 08.11. 08:00-12:00 Digital
2 Stüger , Moodle
Fr 08.11. 08:00-12:00 Digital
3 Stüger , Moodle
Fr 08.11. 08:00-12:00 Digital

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 information is available for each group.

Groups

Group 1

Die Plätze werden vorrangig an Studierende im Masterstudium Ernährungswissenschaften vergeben. Die Einteilung zu den Kursen erfolgt über Moodle

max. 15 participants
Language: German
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

Units from 4.10.-15.11. are lectures,
22.11.-24.1. exercise units (with R).

  • Friday 04.10. 08:00 - 12:00 Digital
  • Friday 11.10. 08:00 - 12:00 Digital
  • Friday 18.10. 08:00 - 12:00 Digital
  • Friday 25.10. 08:00 - 12:00 Digital
  • Friday 15.11. 08:00 - 12:00 Digital
  • Thursday 21.11. 16:30 - 18:00 Digital
  • Friday 22.11. 08:00 - 10:30 Digital
  • Friday 29.11. 08:00 - 10:30 Digital
  • Friday 06.12. 08:00 - 10:30 Digital
  • Friday 13.12. 08:00 - 10:30 Digital
  • Friday 10.01. 08:00 - 10:30 Digital
  • Friday 17.01. 08:00 - 10:30 Digital
  • Friday 24.01. 08:00 - 10:35 Digital
  • Thursday 30.01. 16:30 - 18:00 Digital

Group 2

Die Plätze werden vorrangig an Studierende im Masterstudium Ernährungswissenschaften vergeben. Die Einteilung zu den Kursen erfolgt über Moodle

max. 15 participants
Language: German
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

Units from 4.10.-15.11. are lectures,
22.11.-24.1. exercise units (with R).

  • Friday 04.10. 08:00 - 12:00 Digital
  • Friday 11.10. 08:00 - 12:00 Digital
  • Friday 18.10. 08:00 - 12:00 Digital
  • Friday 25.10. 08:00 - 12:00 Digital
  • Friday 15.11. 08:00 - 12:00 Digital
  • Thursday 21.11. 16:30 - 18:00 Digital
  • Friday 22.11. 11:00 - 13:30 Digital
  • Friday 29.11. 11:00 - 13:30 Digital
  • Friday 06.12. 11:00 - 13:30 Digital
  • Friday 13.12. 11:00 - 13:30 Digital
  • Friday 10.01. 11:00 - 13:30 Digital
  • Friday 17.01. 11:00 - 13:30 Digital
  • Friday 24.01. 11:00 - 13:30 Digital
  • Thursday 30.01. 16:30 - 18:00 Digital

Group 3

Die Plätze werden vorrangig an Studierende im Masterstudium Ernährungswissenschaften vergeben. Die Einteilung zu den Kursen erfolgt über Moodle

max. 15 participants
Language: German
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

Units from 4.10.-15.11. are lectures,
22.11.-24.1. exercise units (with R).

  • Friday 04.10. 08:00 - 12:00 Digital
  • Friday 11.10. 08:00 - 12:00 Digital
  • Friday 18.10. 08:00 - 12:00 Digital
  • Friday 25.10. 08:00 - 12:00 Digital
  • Friday 15.11. 08:00 - 12:00 Digital
  • Thursday 21.11. 16:30 - 18:00 Digital
  • Friday 22.11. 14:00 - 16:30 Digital
  • Friday 29.11. 14:00 - 16:30 Digital
  • Friday 06.12. 14:00 - 16:30 Digital
  • Friday 13.12. 14:00 - 16:30 Digital
  • Friday 10.01. 14:00 - 16:30 Digital
  • Friday 17.01. 14:00 - 16:30 Digital
  • Friday 24.01. 14:00 - 16:30 Digital
  • Thursday 30.01. 16:30 - 18:00 Digital

Information

Aims, contents and method of the course

comprehensive understanding of multivariate methods + terminology: modelling (general linear model incl. repeated measurements, logistic regression), PCA & factor analysis, cluster analysis. Practical exercises with R/R-Studio on the PC
Prerequisites: practical knowledge of R/R Studio is mandatory!
This course is held in 2 parts: 1. lecture 2. practical exercises (online - 3 groups per 18 students). For the practical exercises it is necessary that R and Studio are installed on your personal computer.
Lectures/exercises will all be held digitally.

Assessment and permitted materials

written intermediate exam about lecture contents (90min). Students who have already passed the lecture exam do not need to repeat thist part.
final online exam with R (90min) + delivery of a statistical elaboration on a scientific journal article + participation points in the online practical exercises

You can use all material (paper, electronically) from the lecture, but no web search results or any AI-apps.

Minimum requirements and assessment criteria

45% of the score for the intermediate exam
+ final exam with R (35%) + statistical paper (15%) + activ participation (5%)
grading key (points out of 100): 90+ 1; 77+ 2; 64+ 3; 51+ 4

Examination topics

Contents of the slides and oral lecture + examples from practical exercises

Reading list

lecture slides

Association in the course directory

Last modified: We 02.10.2024 18:26