PROBABILITY THEORY
This chapter begins with a review of elementary probability theory, conditional probability, and statistical independence. It explains the notion of a random variable and its distribution function or probability density function. It then introduces the concepts of mathematical expectation and variance and discusses several distributions often met in practice: the binomial, Gaussian, and Poisson distributions. The characteristic function of a random variable is defined and applied to the determination of the distribution of the sum of independent random variables. The central limit theorem is described but not proved.
Keywords: probability, random variable, Bertand's paradox, distribution, binomial, Gaussian, Poisson, expectation, variance, characteristic function
Oxford Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.
Please, subscribe or login to access full text content.
If you think you should have access to this title, please contact your librarian.
To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us .