The Applied Computational Statistics module covers the fundamental concepts of probability and statistics. Students are taught the methods and techniques to set up statistical models and perform inferential tasks, such as prediction and hypothesis testing. In addition, students will use Python for statistical analysis.

Topics covered include probability theory, special distributions, central tendency, estimation, hypothesis testing, resampling methods, linear models, non-parametric models, and Bayesian statistics, among others.