234001 SE Population Forecasting (2023W)
Prüfungsimmanente Lehrveranstaltung
Labels
VOR-ORT
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Fr 01.09.2023 09:00 bis Fr 22.09.2023 23:59
- Abmeldung bis Fr 22.09.2023 23:59
Details
max. 20 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
Donnerstag
05.10.
15:00 - 18:15
PC-Raum 1 Schenkenstraße 8-10, 1.UG
Donnerstag
07.12.
15:00 - 18:15
PC-Raum 1 Schenkenstraße 8-10, 1.UG
Donnerstag
14.12.
15:00 - 18:15
PC-Raum 1 Schenkenstraße 8-10, 1.UG
Donnerstag
11.01.
15:00 - 18:15
PC-Raum 1 Schenkenstraße 8-10, 1.UG
Donnerstag
18.01.
15:00 - 18:15
PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag
25.01.
15:00 - 18:15
PC-Raum 1 Schenkenstraße 8-10, 1.UG
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. (Home) exercises (30%); to be completed partly in class, partly at home.
2. Midterm exam (30%);
3. Population projections by age and sex to be submitted as a functioning R-code (40%). The goal of this task is to roughly replicate the results according to the UN World Population Prospects.
2. Midterm exam (30%);
3. Population projections by age and sex to be submitted as a functioning R-code (40%). The goal of this task is to roughly replicate the results according to the UN World Population Prospects.
Mindestanforderungen und Beurteilungsmaßstab
Participation is obligatory. Students may miss at most one class.
Grades will be based on the three tasks (exercises, projection code, participation)
All three are obligatory.
Grades will be based on the three tasks (exercises, projection code, participation)
All three are obligatory.
Prüfungsstoff
Literatur
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Di 03.10.2023 10:28