Analyzing dynamical data - from basic statistics to modern time series analysis

given by Dr. Reik Donner

When it comes to analyzing empirical observations or model output data, many researchers commonly resort to basic statistical tools, potentially missing a whole world of detailed information on underlying processes that these simple methods cannot resolve by their construction. This course provides an introduction into the world beyond these classical statistical methods. Starting from corresponding basic analysis tools like correlation functions, common problems are introduced that arise when dealing with real-world time series across scientific disciplines (like handling nonstationarity, trends, periodic components and stochastic persistence), together with mathematical approaches addressing the corresponding conceptual challenges. Besides discussion the underlying concepts and their limitations, a particular focus will be on providing particular examples on how to use these data analysis techniques in common statistical software environments like R or Matlab, and how to interpret the thus obtained results.