Universität Wien

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

Continuous assessment of course work
REMOTE

Summary

1 Stüger , Moodle
2 Stüger , Moodle
3 Stüger , 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).
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

Dates from 5.3.-22.3. + 9.4. are lecture units,
12.4.-14.6. are practical units.

mid-term exam 15.04. 8:00 - 9:30 Digital

final exam 20.06.16:00 - 17:30 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

LV-Termine Gruppe 1 +2

Dienstag 05.03.08:00 - 12:00Digital

Freitag 08.03.08:00 - 12:00 Digital

Freitag 15.03. 08:00 - 12:00 Digital

Dienstag 19.03. 08:00 - 12:00 Digital

Freitag 22.03. 08:00 - 12:00 Digital

Termine Gruppe 2:

Freitag 12.04.11:00-13:30 Digital

Freitag 19.04.11:00 - 13:30Digital

Freitag 26.04.11:00 - 13:30 Digital

Freitag 03.05.11:00 - 13:30 Digital

Freitag24.05.11:00 - 13:30Digital

Freitag 07.06.11:00 - 13:30 Digital

Freitag 14.06.11:00 - 13:30 Digital

Prüfungen (für beide Gruppen):

Dienstag 09.04.16:00 - 17:30 Digital

Donnerstag 20.06.16:00 - 17:30Digital

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

Dates from 5.3.-22.3. + 9.4. are lecture units,
12.4.-14.6. are practical units.

mid-term exam 09.04.16:00 - 17:30 Digital

final exam 20.06.16:00 - 17:30 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: Fr 15.03.2024 13:26