Sipser's candid, crystal-clear style allows students at every level to understand and enjoy this field. His innovative "proof idea" sections explain profound concepts in plain English. The new edition incorporates many improvements students and professors have suggested over the years, and offers updated, classroom-tested problem sets at the end of each chapter.

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    Includes expert coverage of new topics: Turbocodes, Turboequalization, Antenna Arrays, Digital Cellular Systems, and Iterative Detection. Convenient, sequential organization begins with a look at the historyo and classification of channel models and builds from there.

    Next, it introduces the measurement and reporting of cash flows, analysis and interpretation of financial statements; cost-volume-profit analysis; full costing; budgeting, and capital investment decisions. Extensive self-assessment and review questions are included, along with a detailed glossary.

    But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas- sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con- ducted in statistics departments while data mining and machine learning re- search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo- rithms are more scalable than statisticians ever thought possible. Formal sta- tistical theory is more pervasive than computer scientists had realized.

    Unnikrishna Pillai of Polytechnic University. The book is intended for a senior/graduate level course in probability and is aimed at students in electrical engineering, math, and physics departments. The authors' approach is to develop the subject of probability theory and stochastic processes as a deductive discipline and to illustrate the theory with basic applications of engineering interest. Approximately 1/3 of the text is new material--this material maintains the style and spirit of previous editions. In order to bridge the gap between concepts and applications, a number of additional examples have been added for further clarity, as well as several new topics.

    Dozens of examples in innumeracy show us how it affects not only personal economics and travel plans, but explains mis-chosen mates, inappropriate drug-testing, and the allure of pseudo-science.

    The presentation stresses analytical methods, concrete examples, and geometric intuition. A unique feature of the book is its emphasis on applications. These include mechanical vibrations, lasers, biological rhythms, superconducting circuits, insect outbreaks, chemical oscillators, genetic control systems, chaotic waterwheels, and even a technique for using chaos to send secret messages. In each case, the scientific background is explained at an elementary level and closely integrated with mathematical theory.About the Author:Steven Strogatz is in the Center for Applied Mathematics and the Department of Theoretical and Applied Mathematics at Cornell University. Since receiving his Ph.D. from Harvard university in 1986, Professor Strogatz has been honored with several awards, including the E.M. Baker Award for Excellence, the highest teaching award given by MIT.

    But that does not even begin to convey what the Berger experience is: What makes these bestselling textbooks so distinctive is the unmistakable presence of KATHLEEN STASSEN BERGER on every page, in writing that continually draws on the author’s teaching and family life to demonstrate a remarkable understanding not just of the field, but of students’ questions, their concerns, and their lives.The distinctive, definitive BERGER touch is evident throughout her new textbook, Invitation to the Life Span. This brief, original, 15-chapter textbook was created from page 1 to address the challenges teachers and students face when covering the entire life span in a semester (or even a quarter!). The hallmark Berger qualities are all here—the relatable presentation of research, the inclusive approach to world cultures, the study help that builds critical thinking and observational skills, the outstanding media and supplements—and all held together with Berger’s skill in bringing students and the science together.

    Long recognized as very applied and practical, Eggen and Kauchak's Educational Psychology: Windows on Classrooms, seventh edition is now even more applied and concise, giving students exactly what they need to know in the course. The author's hallmark cases remain, in both written and videotape format, to introduce real-world applications in a way that no other text can. Along with expanded applications to diversity (urban, suburban, and rural areas), technology, and a new pedagogical system that completely restructures how information is delivered in the book and will help students really understand what they should be getting out of every single chapter. The text now comes with two new DVDs of video material and an access code for the new Teacher Prep Website that will be automatically shrinkwrapped with all new copies of the text. Educational Psychology: Windows on Classrooms once again truly fulfills the promise of its title, giving students a window on the classrooms in which they will someday teach.

    Because the job of a manager is to make financial decisions that increase firm value, the authors have embedded real-world mini-cases throughout to apply chapter concepts to the types of situations managers of multinational firms face.

    Readers profit from its verbal-conceptual exposition and frequent use of examples.The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying website with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT, at www.psypress.com/9780805822236 .Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.

    It blends practical and theoretical coverage, while maintaining an appropriate rigor and a clear writing style. Its unifying theme is that security markets are nearly efficient, meaning that most securities are priced appropriately given their risk and return attributes. The text places greater emphasis on asset allocation and offers a much broader and deeper treatment of futures, options, and other derivative security markets than most investment texts. It is also the only graduate Investments text to offer an online homework management system, McGraw-Hill's "Connect Finance."

    They'll also find the related analytic geometry much easier. The clear review of algebra and geometry in this edition will make calculus easier for students who wish to strengthen their knowledge in these areas. Updated to meet the emphasis in current courses, this new edition of a popular guide--more than 104,000 copies were bought of the prior edition--includes problems and examples using graphing calculators..