Methoden der Datenwissenschaft

What it is about

You will learn central methods of Frequentist and Bayesian data analysis: estimation theory, hypothesis testing, confidence intervals as well as Bayesian inference with MCMC, variational inference and ABC. In the end you will be able to perform statistical inference, fit simple models, compute error estimates and use standard statistics packages (e.g. scipy) for analysis.

What you will be able to do

• use scipy and similar statistics packages
• calculate descriptive statistics
• perform simple model fitting
• compute and quantify errors
• perform frequentist inference (estimation, tests, confidence intervals)
• perform Bayesian inference (closed forms, MCMC, variational methods, ABC)

What the module consists of

• VorlesungExplanation of theoretical concepts and introduction of new tools and methods (90 minutes, Tuesdays)
• ÜbungenPractical implementation of lecture content on the console/computer using exercises, usually with Jupyter notebooks

Teaching method

• Präsenzvorlesung (ggf. Live-Stream)Conveying the theoretical foundations and new methods
• Praktische Übungen am ComputerPractise and apply the methods using tasks and notebooks