Data Analysis and Stochastic Modelling
Winter Semester 2023/2024
The course takes place on Thursdays starting at 12:30 in room 28.2.123. It consists of 2SWS Lectures and 2SWS with practical programming exercises (1 SWS for Bachelor courses). The execises take place on Thursdays at 16:00 in room 28.0.087.
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- Chapter 1: Predictions (HTML 6KB)
- Chapter 2: Brownian Motion (HTML 8KB)
- Chapter 3: Autocorrelations (HTML 8KB)
- Chapter 4: Chaos (HTML 9KB)
- Chapter 5: Non-Gaussianity (HTML 15KB)
- Chapter 6: Time Reversal Symmetry (HTML 6KB)
- Chapter 7: Active Motion (HTML 7KB)
- Chapter 8: Spectral Methods (HTML 12KB)
- Chapter 11: Autoregressive Models (HTML 10KB)
- Chapter 12: Supervised Learning (HTML 9KB)
- Chapter 13: Causality (HTML 7KB)
- Exercise 1: Random Walks (HTML 4KB)
- Exercise 2: Pseudo-Brownian Motion (HTML 4KB)
- Exercise 3: Financial Time Series (HTML 3KB)
- Exercise 4: Climate in Potsdam (HTML 3KB)
- Exercise 5: Politics (HTML 4KB)
- Exercise 6: Avogadro Constant (HTML 5KB)
- Exercise 7: Wind Speed (HTML 4KB)
- Exercise 8: Sunspots (HTML 5KB)