Welcome

Welcome to website of the course “Introduction to Bayesian Inference and Statistical Learning.” offered by the Chair of Spatial Data Science and Statistical Learning at the University of Goettingen.

This course is designed to equip you with both the theoretical foundations and practical tools necessary for applying Bayesian and statistical learning approaches to real-world data. By the end of the course, you will be able to implement various statistical models and conduct analyses of complex datasets using state-of-the-art software.

The content of the course includes foundations of statistical inference, focusing on both frequentist and Bayesian approaches. You will learn about regression models, Bayesian estimation techniques, and advanced statistical learning methods, including supervised and unsupervised learning. We will also explore complex models such as generalized additive models for location, scale, and shape (GAMLSS), as well as techniques for handling high-dimensional data.

In this course portal, you will find a comprehensive script of the material covered in the lecture. You can easily navigate to the lecture of interest using the overview on the left. In each lecture you can browse through the lecture content using the navigation bar on the right. In addition to the core lecture material, this book also provides extended information and interactive elements, including Shiny apps, to enhance your learning experience and support your understanding of the topics. By engaging with this material, including the interactive tools, you will gain a comprehensive understanding of both the theoretical aspects of inference and its practical applications in data analysis.

For further information, visit our chair’s website. Feel free to reach out if you have any questions or need additional support during the course. Also, check out the extensive collection of Shiny apps available at our chair to deepen your statistical knowledge.