Universität Wien
Achtung! Das Lehrangebot ist noch nicht vollständig und wird bis Semesterbeginn laufend ergänzt.

234001 SE Population Forecasting (2024W)

4.00 ECTS (2.00 SWS), SPL 23 - Soziologie
Prüfungsimmanente Lehrveranstaltung
Moodle
Do 23.01. 16:45-18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß

An/Abmeldung

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

Details

max. 20 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Donnerstag 28.11. 15:00 - 18:15 PC-Raum 1 Schenkenstraße 8-10, 1.UG
  • Donnerstag 05.12. 15:00 - 18:15 PC-Raum 1 Schenkenstraße 8-10, 1.UG
  • Donnerstag 12.12. 15:00 - 18:15 Digital
  • Donnerstag 09.01. 15:00 - 18:15 PC-Raum 1 Schenkenstraße 8-10, 1.UG
  • Donnerstag 16.01. 15:00 - 18:15 PC-Raum 1 Schenkenstraße 8-10, 1.UG
  • Donnerstag 30.01. 16:45 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

This course is dedicated to population forecasting based on the R Statistical Software. Using simple examples from R, participants will first learn common techniques of data visualization that will proof helpful during the remainder of the course. After that, different prognostic techniques and their applications will be introduced. An essential aspect of the class will be the development of scenarios, which is key for any meaningful future projection. The main objective of the course is to improve the participants’ understanding of the evolution of population-based processes.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Achievement of that goal will be assessed based on three criteria.

1. Active participation (20%); this includes carrying out at least one programming task in front of the class.
2. Projection exercise (30%); to be submitted as a running R-code by January 7th.
3. Final exam (50%); with programming tasks based on the course-content.

Mindestanforderungen und Beurteilungsmaßstab

Participation is obligatory. Students may miss at most one class.

Grades will be based on the three tasks (participation, projection exercise, final exam)

All three of them are mandatory. Failing to fulfill one of the tasks cannot be compensated by any of the others and leads to a negative grade overall.

Prüfungsstoff

The final exam will consist of programming tasks based on the content of the class.

Literatur

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Do 28.11.2024 13:06