Probability and Statistics

This course gives an introduction to probability and statistics. Uncertainty shows up in many places within computer science. In complex systems you may need to consider failure rates of components, communication delays or imprecision in data or sensor input, whereas in algorithms randomness is used as a tool to create simpler or faster solutions. In these situations considering only best and worst-case behavior leads a an overly optimistic or pessimistic representation. Instead, a better option is often to model this uncertainty and analyze the model. Probability theory gives us the tools to do this and get a more accurate representation of the behavior of complex systems or algorithms. Statistics, on the other hand, concerns what can be learned from data. In this course you will learn how to build and analyse probabilistic models, perform basic procedures in statistics, and the theory behind all this.