Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture introduces the concept of random number generators (RNGs), focusing on uniform random number generators and pseudo-random number generators. It covers the definition, general structure, properties, and examples of RNGs, such as Linear Congruential Generators (LCG) and Multiple Recursive Generators (MRG). The lecture also discusses combined generators and the assessment of RNG quality through empirical tests. Additionally, it explores non-parametric goodness-of-fit tests like Q-Q plots and the Kolmogorov-Smirnov Test.