《应用随机过程概率模型导论(英文版·第9版)》叙述深入浅出，涉及面广。主要内容有随机变量、条件概率及条件期望、离散及连续马尔可夫链、指数分布、泊松过程、布朗运动及平稳过程、更新理论及排队论等；也包括了随机过程在物理、生物、运筹、网络、遗传、经济、保险、金融及可靠性中的应用。特别是有关随机模拟的内容，给随机系统运行的模拟计算提供了有力的工具。除正文外，《应用随机过程概率模型导论(英文版·第9版)》有约700道习题，其中带星号的习题还提供了解答。 《应用随机过程概率模型导论(英文版·第9版)》可作为概率论与统计、计算机科学、保险学、物理学、社会科学、生命科学、管理科学与工程学等专业随机过程基础课教材。

The new Second Edition will extend coverage to regression models such as: generalized linear models; limited-dependent-variable-models; mixed models and Cox regression among other methods.

Editorial Reviews Product Description Develop a conceptual understanding of statistical ideas and learn to find meaning in data with MIND ON STATISTICS and its accompanying online learning tools. Utts and Heckard explain statistical topics through excellent examples and case studies, balancing the spirit of statistical literacy with the statistical methodology. You'll develop your statistical intuition by focusing on analyzing data and interpreting results, rather than on mathematical formulation.Your purchase includes access to iLrn Homework, an online tool that guides you through problem solving, as well as access to a live online tutor and an online university library. About the Author Jessica Utts is a Professor of Statistics at the University of California at Davis, where she joined the faculty in 1978. She received her B.A. in Math and Psychology at SUNY Binghamton, and her M.A. and Ph.D. in Statistics at Penn State University. She is the author of SEEING THROUGH STATISTICS (3rd edition, 2005) and the co-author with Robert Heckard of STATISTICAL IDEAS AND METHODS (1st edition, 2006) both published by Duxbury Press. She is also the Editor-in-Chief of CYBERSTATS, an interactive online introductory statistics course. Jessica has been active in the Statistics Education community at the high school and college level. She served as a member and then chaired the Advanced Placement Statistics Development Committee for six years, and was a member of the American Statistical Association task force that produced the GAISE (Guidelines for Assessment and Instruction in Statistics Education) recommendations for Elementary Statistics courses. She is the recipient of the Academic Senate Distinguished Teaching Award and the Magnar Ronning Award for Teaching Excellence, both at the University of California at Davis. She is also a Fellow of the American Statistical Association, the Institute of Mathematical Statistics and the American Association for the Advancement of Science. Beyond statistics education Jessica's major contributions have been in applying statistics to a variety of disciplines, most notably to parapsychology, the laboratory study of psychic phenomena. She has appeared on numerous television shows, including Larry King Live, ABC Nightline, CNN Morning News and 20/20, and most recently appears in a documentary included on the DVD with the movie "Suspect Zero." Robert F. Heckard is a senior lecturer in statistics at the Pennsylvania State University, where he has taught for over 30 years. He has taught introductory and intermediate applied statistics to more than 15,000 college students. Bob has been awarded several grants to develop multimedia and web-based instructional materials for teaching statistical concepts. He is the co-author of STATISTICAL IDEAS AND METHODS (1st edition, 2006, Duxbury Press) and is a co-author of CYBERSTATS, a web-based introductory course. As a consultant, he is active in the statistical analysis and design of highway safety research and has frequently been a consultant in cancer treatment clinical trials.

The high-level language of R is recognized as one of the most powerful and flexible statistical software environments, and is rapidly becoming the standard setting for quantitative analysis, statistics and graphics. R provides free access to unrivalled coverage and cutting-edge applications, enabling the user to apply numerous statistical methods ranging from simple regression to time series or multivariate analysis. Building on the success of the author’s bestselling Statistics: An Introduction using R, The R Book is packed with worked examples, providing an all inclusive guide to R, ideal for novice and more accomplished users alike. The book assumes no background in statistics or computing and introduces the advantages of the R environment, detailing its applications in a wide range of disciplines. * Provides the first comprehensive reference manual for the R language, including practical guidance and full coverage of the graphics facilities. * Introduces all the statistical models covered by R, beginning with simple classical tests such as chi-square and t-test. * Proceeds to examine more advance methods, from regression and analysis of variance, through to generalized linear models, generalized mixed models, time series, spatial statistics, multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates and professionals in science, engineering and medicine. It is also ideal for students and professionals in statistics, economics, geography and the social sciences.

《统计与真理:怎样运用偶然性》是当代国际最著名的统计学家之一C.R.劳的一部统计学哲理论著，也是他毕生统计学术思想的总结，同时还是一本通俗的关于统计学原理的普及教科书。书中，作者从哲学的角度论述了统计学原理，通过实例，不仅证明了统计学是一门最严格、最合理的认识论和方法学，还深刻地揭示了现代统计学发展的过程，特别是那些很深刻的理论是如何从一些非常简单实际的问题中发展起来的。《统计与真理:怎样运用偶然性》前5章讲述了统计学从最初收集、汇编数据为行政管理服务，发展成为有一整套原理和研究方法的独立学科的历史，第6章谈及了普通公众对统计学的理解，强调了从数字中学习有助于成为有效率的公民，《统计与真理:怎样运用偶然性》最引人注目的特点是，书中提到的所有科学的学科调查与决策和统计之间的关联是由一系列实例来说明的。《统计与真理:怎样运用偶然性》使用非专业语言通俗地阐述了统计学的基本概念和方法，适合大众读者。

A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field.