Inhoudsopgave:
|
\u003cb\u003eINTRODUCTION TO PROBABILITY\u003c/b\u003e \u003cp\u003e\u003cb\u003eDiscover practical models and real-world applications of multivariate models useful in engineering, business, and related disciplines\u003c/b\u003e \u003cp\u003eIn \u003ci\u003eIntroduction to Probability: Multivariate Models and Applications, \u003c/i\u003ea team of distinguished researchers delivers a comprehensive exploration of the concepts, methods, and results in multivariate distributions and models. Intended for use in a second course in probability, the material is largely self-contained, with some knowledge of basic probability theory and univariate distributions as the only prerequisite. \u003cp\u003eThis textbook is intended as the sequel to\u003ci\u003e Introduction to Probability: Models and Applications.\u003c/i\u003e Each chapter begins with a brief historical account of some of the pioneers in probability who made significant contributions to the field. It goes on to describe and explain a critical concept or method in multivariate models and closes with two collections of exercises designed to test basic and advanced understanding of the theory. \u003cp\u003eA wide range of topics are covered, including joint distributions for two or more random variables, independence of two or more variables, transformations of variables, covariance and correlation, a presentation of the most important multivariate distributions, generating functions and limit theorems. This important text: \u003cul\u003e\u003cli\u003eIncludes classroom-tested problems and solutions to probability exercises \u003c/li\u003e \u003cli\u003eHighlights real-world exercises designed to make clear the concepts presented \u003c/li\u003e \u003cli\u003eUses Mathematica software to illustrate the text\u0026#8217;s computer exercises\u003c/li\u003e \u003cli\u003eFeatures applications representing worldwide situations and processes \u003c/li\u003e \u003cli\u003eOffers two types of self-assessment exercises at the end of each chapter, so that students may review the material in that chapter and monitor their progress\u003c/li\u003e\u003c/ul\u003e \u003cp\u003ePerfect for students majoring in statistics, engineering, business, psychology, operations research and mathematics taking a second course in probability, \u003ci\u003eIntroduction to Probability: Multivariate Models and Applications\u003c/i\u003e is also an indispensable resource for anyone who is required to use multivariate distributions to model the uncertainty associated with random phenomena. |
nl
en