Module MA4341-KP05

Duration

1 Semester

Turnus of offer

irregularly

Credit points

5

Course of studies, specific fields and terms:

• Master CLS 2023, optional subject, mathematics
• Bachelor CLS 2023, optional subject, mathematics
• Minor in Teaching Mathematics, Master of Education 2023, optional subject, mathematics
• Minor in Teaching Mathematics, Master of Education 2017, optional subject, mathematics
• Master CLS 2016, optional subject, mathematics
• Bachelor CLS 2016, optional subject, mathematics

Classes and lectures:

• Time series analysis (exercise, 1 SWS)
• Time series analysis (lecture, 2 SWS)

Workload:

• 45 hours in-classroom work
• 85 hours private studies and exercises
• 20 hours exam preparation

Contents of teaching:

• Simple discriptive and explorative methods: smoothing, differentiating, autocorrelation, cross correlation
• Linear time series models: MA-processes, AR-processes, ARIMA-processes
• Time series and models with long-range dependencies
• Time series in the frequency domain: autocorrelation function, spectral density and its estimation
• nonlinear methods by examples
• analysis and modelling of data from life sciences (software: R, Mathematica, SPSS)

Qualification-goals/Competencies:

• Students have basic knowledge of concepts and ideas of time series analysis
• They master simple linear methods of time series analysis
• They have competencies in analysis and modelling of real-world time series

Grading through:

• Oral examination

Requires:

• Stochastics 2 (MA4020-KP07)

Responsible for this module:

• Nachfolge von Prof. Dr. rer. nat. Karsten Keller

Teacher:

• Institute for Mathematics
• Nachfolge von Prof. Dr. rer. nat. Karsten Keller

Literature:

• R. Schlittgen, B.Streitberg : Zeitreihenanalyse Oldenburg-Verlag, München, Wien 1994
• P.J. Brockwell, R.A. Davis : Time Series: Theory and Methods Springer, New York 1991

Language:

• offered only in German

Notes:

Last Updated:

22.02.2022