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

290435 PS Applied Time Series Analysis (2016S)

4.00 ECTS (2.00 SWS), SPL 29 - Geographie
Prüfungsimmanente Lehrveranstaltung

This course is taught in English. The lecturer speaks German too, so don't be scared.
Moodle

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: Deutsch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Mittwoch 09.03. 17:00 - 21:00 Seminarraum Geographie NIG 5.OG C0528
  • Mittwoch 16.03. 17:00 - 21:00 Seminarraum Geographie NIG 5.OG C0528
  • Mittwoch 13.04. 17:00 - 21:00 Seminarraum Geographie NIG 5.OG C0528
  • Mittwoch 20.04. 17:00 - 21:00 Seminarraum Geographie NIG 5.OG C0528
  • Mittwoch 04.05. 17:00 - 21:00 Seminarraum Geographie NIG 5.OG C0528
  • Mittwoch 08.06. 17:00 - 21:00 Seminarraum Geographie NIG 5.OG C0528
  • Mittwoch 15.06. 17:00 - 21:00 Seminarraum Geographie NIG 5.OG C0528

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

This course builds upon the introductory statistic courses. After a brief recapitulation, the course continues from there and aims at equipping students with a toolset of statistical methods in the field of time series analysis (Time Series Analysis and Its Application by Shumway & Stoffer). This toolset should enable students to conduct statistical research on time series completely independently and comprises (see more details below) time series regression, decomposition of time series into components and the analysis of these components with the statistical package R.
The course covers theory that is applied to real data and is therefore primarily focused on applications and the acquisition of practical skills.

1. Recap: linear regression and its assumptions; introduction to R
2. Characteristics of Time Series & Stationarity
3. Time Series Regression and Exploratory Data Analysis
4. ARIMA Models
5. Spectral Analysis and Filtering
6. Unit Root Testing
7. Additional Time Domain Topics

Students are also invited to BYOP (bring your own problems) to class early on.

Each unit comprises a theoretical part and an applied part. In the applied part students foster their new theoretic knowledge by testing real world data in the statistical software R. For this second part computer equipment is necessary. Students will work on a project of their choice which they will present to the class in the later part of the course. The class will then discuss the work.

Art der Leistungskontrolle und erlaubte Hilfsmittel

The grading is based on the following

.) A short multiple choice test at the end of the semester (35%)
.) The presentation of the project work (35%)
.) Homework (30%)

Mindestanforderungen und Beurteilungsmaßstab

Minimum requirements for a positive mark: 50% of total score and positive end test.

Prüfungsstoff

Main Literature

Shumway, R. and Stoffer, D. (2010). Time Series Analysis and Its Applications: With R Examples. Springer Texts in Statistics. Springer.

Literatur

Further Literature

Brockwell, P. J. and Davis, R. A. (2006). Introduction to time series and forecasting. Springer Science & Business Media.

Hackl, P. (2008). Einführung in die Ökonometrie. Pearson Studium – Economic BWL. Pearson Studium.

James, G., Witten, D., Hastie, T., and Tibshirani, R. (2014). An Introduction to Statistical Learning: with Applications in R. Springer Texts in Statistics. Springer New York.

Kleiber, C. and Zeileis, A. (2008). Applied Econometrics with R. Springer.

Montgomery, D. C., Jennings, C. L., and Kulahci, M. (2015). Introduction to time
series analysis and forecasting. John Wiley & Sons.

Wooldridge, J. (2009). Introductory Econometrics: A Modern Approach: A Modern Approach. ISE - International Student Edition. South Western, Cengage Learning.

Wooldridge, J. M. (2002). Econometric Analysis of Cross Section and Panel Data. MIT press.

Zuordnung im Vorlesungsverzeichnis

(MG-W3-PI) (MG-W5-PI) (MG-W6-PI) (MR1-PI) (MR6-PI) (L2-FW) (D5)

Letzte Änderung: Mo 07.09.2020 15:42