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 ...

In the early development of probability theory, only discrete random variables (although not called random variables at the time) were considered. Isaac Newton (1643-1727) considered the idea of ...

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

Abstract: Since in most applications, the distribution of the random variable of interest is not known, the collection of a data set relating to the random variable, and presenting and analyzing the ...

Implementation of the projects for the DSC 530: Probability and Statistics for Data Science course, of the MSc in Data Science programme of the University of Cyprus.

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, ...

📈📄👀A lookup repo for a variety of discrete and continuous distributions (incl. Beta, Binomial, Cauchy, Chi-squared, Geometric, Hypergeometric, Normal & Poisson) ...

Abstract: In this chapter, analysis and processing of random processes is presented. After introducing stochastics continuity, differentiation, and integration, we briefly discuss power spectral ...