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Modul
Time Series Analysis [M-MATH-102911]
Credits
4Recurrence
Jedes SommersemesterDuration
1 SemesterLanguage
Level
4Version
2Responsible
Organisation
- KIT-Fakultät für Mathematik
Part of
Bricks
Identifier | Name | LP |
---|---|---|
T-MATH-105874 | Time Series Analysis | 4 |
Competence Certificate
The module will be completed by an oral exam (ca. 20 min).
Competence Goal
At the end of the course, students will
- know and understand the standard models of time series analysis,
- know exemplary statistical methods for model selection and model validation,
- independently apply models and methods from the lecture to real and simulated data,
- know specific mathematical techniques and be able to use them to analyze time series models.
Prerequisites
None
Content
The lecture covers the basic concepts of classical time series analysis:
- Stationary time series
- Trends and seasonality
- Autocorrelation
- Autoregressive models
- ARMA models
- Parameter estimation
- Forecasting
- Spectral density and periodogram
Recommendation
The contents of the course "Probability Theory" are strongly recommended. The contents of the course "Statistics" are recommended.
Workload
Total workload: 120 hours
Attendance: 45 hours
- lectures, problem classes, and examination
Self-studies: 75 hours
- follow-up and deepening of the course content,
- work on problem sheets,
- literature study and internet research relating to the course content,
- preparation for the module examination