This course covers topics such as overview of sets, counting principles, probability, conditional probability and Bayes’ Rule, discrete Random Variables, continuous Random Variables, Bayesian ...

Conditional Probability We start the section off with an introduction to conditional probability. We look at the difference between dependent and independent events, look at how to calculate dependent ...

This course provides an introduction to probability models including sample spaces, mutually exclusive and independent events, conditional probability and Bayes' Theorem. The named distributions ...

Course Overview This course is the first part of a two-semester sequence with MAT 314, with a focus on basic probability. It covers descriptive statistics, sample spaces and events, axioms of ...

Introduction to random variation and probability: probability axioms. Counting arguments. Conditional probability and independence. Discrete probability models: the binomial, geometric and Poisson ...

This article is meant to serve as an introduction to the following series of papers on various aspects of conditional event algebra and probability logic. It ad ...

Inspired by works on the Markov process based steganalysis, we propose a new steganalysis technique based on the conditional probability statistics. Specifically we focus on its performance against ...