Modul

The module will be completed by an oral exam (ca. 20 min).

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.

None

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

The contents of the course "Probability Theory" are strongly recommended. The contents of the course "Statistics" are recommended.

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