Ross's classic bestseller, Introduction to Probability Models, has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. It provides an introduction to elementary probability theory and stochastic processes, and shows how probability theory can be applied to the study of phenomena in fields such as engineering,...(展开全部)

Ross's classic bestseller, Introduction to Probability Models, has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. It provides an introduction to elementary probability theory and stochastic processes, and shows how probability theory can be applied to the study of phenomena in fields such as engineering,...(展开全部)

Ross' classic bestseller, "Introduction to Probability Models", has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. It provides an introduction to elementary probability theory and stochastic processes, and shows how probability theory can be applied to the study of phenomena in fields such as engineering, ...(展开全部)

Introduction to Probability Models, Twelfth Edition, is the latest version of Sheldon Ross's classic bestseller. This trusted book introduces the reader to elementary probability modelling and stochastic processes and shows how probability theory can be applied in fields such as engineering, computer science, management science, the physical and social sciences and operations r...(展开全部)

Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and toolsfor understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored incl...(展开全部)

Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and toolsfor understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored incl...(展开全部)

Assuming no prior knowledge of linguistics, AN INTRODUCTION TO LANGUAGE, Tenth Edition, is appropriate for a variety of fields--including education, languages, psychology, cognitive science, anthropology, English, and teaching English as a Second Language (TESL)--at both the undergraduate and graduate levels. This completely updated edition retains the clear descriptions, humor...(展开全部)

Assuming no prior knowledge of linguistics, AN INTRODUCTION TO LANGUAGE, Tenth Edition, is appropriate for a variety of fields--including education, languages, psychology, cognitive science, anthropology, English, and teaching English as a Second Language (TESL)--at both the undergraduate and graduate levels. This completely updated edition retains the clear descriptions, humor...(展开全部)

Dimitri P. Bertsekas，美国工程院院士，IEEE会士。1971年获MIT电子工程博士学位。长期在MIT执教，曾获得2001年度美国控制协会 J. Ragazzini 教育奖。研究领域涉及优化、控制、大规模计算、数据通信网络等，许多研究具有开创性贡献。著有 Nonlinear Programming 等十余部教材和专著，其中许多被MIT等名校用作研究生或本科生教材。 John N. Tsitsiklis，美国工程院院士，IEEE会士，MIT教授。分别于1980年、1981年、1984年在MIT获得学士、硕士、博士学位。已发表学术论文上百篇。