Universität Wien

300065 VU Quantitative analysis of time series and population data (2025W)

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

Dieser Kurs gehört im Modul MNB2 zum Bereich Datenanalyse und -modellierung.
Moodle
Mi 19.11. 13:15-16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1

An/Abmeldung

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

Details

max. 25 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Donnerstag 02.10. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Donnerstag 09.10. 09:45 - 11:15 Seminarraum 3.1, Biologie Djerassiplatz 1, 3.124, Ebene 3
  • Donnerstag 16.10. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Donnerstag 23.10. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Donnerstag 30.10. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Donnerstag 06.11. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Mittwoch 12.11. 13:15 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Donnerstag 13.11. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Donnerstag 20.11. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Mittwoch 26.11. 13:15 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Donnerstag 27.11. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Mittwoch 03.12. 13:15 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Donnerstag 04.12. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Mittwoch 10.12. 13:15 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Donnerstag 11.12. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Mittwoch 17.12. 13:15 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Donnerstag 18.12. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Mittwoch 07.01. 13:15 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Donnerstag 08.01. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Mittwoch 14.01. 13:15 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Donnerstag 15.01. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Mittwoch 21.01. 13:15 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Donnerstag 22.01. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1
  • Mittwoch 28.01. 13:15 - 16:30 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Donnerstag 29.01. 09:45 - 11:15 Seminarraum 1.7, Biologie Djerassiplatz 1, 1.010, Ebene 1

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Learning objectives

The students will be able to conduct a basic quantitative and statistical analysis of time series data and data from population samples.
The students have a general understanding of time series data and will be able to perform different interpolation, regression, and fitting techniques on it. They know statistical tools of time series analysis and general time series modelling approaches, and are able to apply them to a given dataset.
The students understand the basic properties of population sampled data. They are able to perform a density estimation on that data, and fit the result to either a single parametrized distribution or a mixture of multiple distributions.
Students are able to perform the discussed analysis techniques in Python, and can interpret their analysis results from time series or population data in a biological context.

Contents

Time series analysis: basic properties, analysis techniques, statistics, models
Population data analysis: density estimation, distribution fitting, mixture modelling
Basic statistical tools: covariance analysis, maximum likelihood estimation, confidence intervals

Methods

Lecture, computer exercise, activities on the online learning platform

Art der Leistungskontrolle und erlaubte Hilfsmittel

- Written exam (60%)
- Solutions of computer exercises (20%)
- Student activity (20%)

Mindestanforderungen und Beurteilungsmaßstab

All partial evaluations must be positive to pass the course. Minimum score to pass is 50% in total.

Prüfungsstoff

In the exam, students need to show that they are able to apply the methods discussed in the course to biological data analysis problems.

Literatur

Literature references are provided in the lecture handouts on Moodle.

Zuordnung im Vorlesungsverzeichnis

MEC-5, MEC-9, MNB2, MBO 7, MZO3, MES4

Letzte Änderung: Mo 29.09.2025 21:27