The Monte Carlo simulation estimates the probability of different outcomes in a process that cannot easily be predicted because of the potential for random variables.

A courseware module that covers the fundamental concepts in probability theory and their implications in data science. Topics include probability, random variables, and Bayes' Theorem.

Abstract: It is well known that the entropy H(X) of a discrete random variable X is always greater than or equal to the entropy H(f(X)) of a function f of X, with equality if and only if f is ...

A variation of a puzzle called the “pick-up sticks problem” asks the following question: If I have some number of sticks with random lengths between 0 and 1, what are the chances that no three of ...

Tristan Jurkovich began his career as a journalist in 2011. His childhood love of video games and writing fuel his passion for archiving this great medium’s history. He dabbles in every genre, but ...

Waseem is a writer here at GameRant. He can still feel the pain of Harry Du Bois in Disco Elysium, the confusion of Alan Wake in the Remedy Connected Universe, the force of Ken's shoryukens and the ...

People are generally bad at producing random actions, but now it seems that we are all uniquely bad in our own way. This makes it possible to predict how an individual will act randomly, which could ...

Many cybersecurity leaders kick off each new year with predictions for the year to come. You may have seen a deluge of them over the last month or so: "Cyberattacks will continue to be a problem." ...