Introduction To Probability An With Mathematica R
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Introduction to Probability with Mathematica
Newcomers to the world of probability face several potential stumbling blocks. They often struggle with key concepts-sample space, random variable, distribution, and expectation; they must regularly confront integration, infrequently mastered in calculus classes; and they must labor over lengthy, cumbersome calculations. Introduction to Probability with Mathematica is a groundbreaking text that uses a powerful computer algebra system as a pedagogical tool for learning and using probability. Its clever use of simulation to illustrate concepts and motivate important theorems gives it an important and unique place in the library of probability theory. The author smoothly integrates the technology with the traditional approach and subject matter, thereby augmenting rather than overpowering it. This book lives and breathes in the sense that not only can it be read and studied in an armchair, but each section also exists as a fully executable Mathematica® notebook on the CRC Web site. Students will find Introduction to Probability with Mathematica an engaging, accessible, yet challenging way to venture into the fascinating subject of probability.
Handbook of Discrete and Combinatorial Mathematics
Handbook of Discrete and Combinatorial Mathematics provides a comprehensive reference volume for mathematicians, computer scientists, engineers, as well as students and reference librarians. The material is presented so that key information can be located and used quickly and easily. Each chapter includes a glossary. Individual topics are covered in sections and subsections within chapters, each of which is organized into clearly identifiable parts: definitions, facts, and examples. Examples are provided to illustrate some of the key definitions, facts, and algorithms. Some curious and entertaining facts and puzzles are also included. Readers will also find an extensive collection of biographies. This second edition is a major revision. It includes extensive additions and updates. Since the first edition appeared in 1999, many new discoveries have been made and new areas have grown in importance, which are covered in this edition.
The Theory of Probability
Another title in the reissued Oxford Classic Texts in the Physical Sciences series, Jeffrey's Theory of Probability, first published in 1939, was the first to develop a fundamental theory of scientific inference based on the ideas of Bayesian statistics. His ideas were way ahead of their time and it is only in the past ten years that the subject of Bayes' factors has been significantly developed and extended. Until recently the two schools of statistics (Bayesian and Frequentist) were distinctly different and set apart. Recent work (aided by increased computer power and availability) has changed all that and today's graduate students and researchers all require an understanding of Bayesian ideas. This book is their starting point.