Extropy has emerged as a pivotal measure in the quantification of uncertainty, serving as a complementary counterpart to the traditional concept of entropy. Unlike entropy, which is widely used to ...

Introduction to probability theory and its applications. Axioms of probability, distributions, discrete and continuous random variables, conditional and joint distributions, correlation, limit laws, ...

Statistical models based on Gaussian random variables occupy a central position in modern data analysis, offering a mathematically tractable framework for inference, prediction and dimensionality ...

This course builds a rigorous foundation of probability. Topics covered include: basic concepts of probability theory and statistics, counting, axioms of probability, independence, Bayes rule, ...