The text is non-threatening and presents concepts clearly and succinctly with a conversational writing style. All statistical concepts are illustrated with solved applied examples immediately upon introduction. Self reviews and exercises for each section, and review sections for groups of chapters also support the student learning steps. Modern computing applications (Excel, Minitab, and MegaStat) are introduced, but the text maintains a focus on presenting statistics concepts as applied in business as opposed to technology or programming methods. The thirteenth edition continues as a students' text with increased emphasis on interpretation of data and results.

    Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory.All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points.The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated referencesNow current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.

    This edition also features the developments in Operations Research, such as metaheuristics, simulation, and spreadsheet modeling.

    Reflecting the need for even minor programming in today's model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work.The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation.By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling.Web ResourceThe book is accompanied by an R package (rethinking) that is available on the author's website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

    Great care has been taken to select important concepts and to perfectly describe the anatomy of cells, organs, and organ systems. The plan that has been followed for eight editions of this text is to combine clear and accurate descriptions of anatomy with precise explanations of how structures function and examples of how they work together to maintain life. To emphasize the concepts of anatomy and physiology, the authors provide explanations of how the systems respond to aging, changes in physical activity, and disease, with a special focus on homeostasis and the regulatory mechanisms that maintain it. Timely and interesting examples demonstrate the application of knowledge in a clinical context.

    The book teaches MATLAB as a technical programming language showing students how to write clean, efficient, and well-documented programs. It makes no pretense at being a complete description of all of MATLAB's hundreds of functions. Instead, it teaches students how to locate any desired function with MATLAB's extensive on line help facilities. Overall, students develop problem-solving skills and are equipped for future courses and careers using the power of MATLAB.

    This title is aimed at courses in applied econometrics, political methodology, and sociological methods or a one-year graduate course in econometrics for social scientists.

    A concise, chronological history of Latin America spans six centuries and encompasses twenty countries as it discusses the people, events, and factors that shaped Latin America--including colonization, revolution, ethnic diversity, and the struggle for economic growth and political and social equality.

    The book will teach you about:* Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data* Deep learning, a powerful set of techniques for learning in neural networksNeural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you the core concepts behind neural networks and deep learning.

    What is the meaning of life? What was Hitler's religion? What's the deal with the Flying Spaghetti Monster? And what was Mother Teresa's dark secret? This book is highly recommended for everyone curious about America's most misunderstood minority, as well as for those who wish to better understand their atheist friends, neighbors or coworkers.

    With this hands-on guide, you'll learn how to write effective, idiomatic Python code by leveraging its best and possibly most neglected features. Author Luciano Ramalho takes you through Python's core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time.Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.This book covers:Python data model: understand how special methods are the key to the consistent behavior of objectsData structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode ageFunctions as objects: view Python functions as first-class objects, and understand how this affects popular design patternsObject-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritanceControl flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packagesMetaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work"

    Drawing heavily on the author's own real-world experiences, the book stresses design and analysis. Coverage is divided into two parts, the first being a general guide to techniques for the design and analysis of computer algorithms. The second is a reference section, which includes a catalog of the 75 most important algorithmic problems. By browsing this catalog, readers can quickly identify what the problem they have encountered is called, what is known about it, and how they should proceed if they need to solve it. This book is ideal for the working professional who uses algorithms on a daily basis and has need for a handy reference. This work can also readily be used in an upper-division course or as a student reference guide. THE ALGORITHM DESIGN MANUAL comes with a CD-ROM that contains: * a complete hypertext version of the full printed book. * the source code and URLs for all cited implementations. * over 30 hours of audio lectures on the design and analysis of algorithms are provided, all keyed to on-line lecture notes.

    These two highly-respected economists and educators have revised this best-selling MICRO FIRST book to include more current topics and events while maintaining its hallmark feature of teaching economics through stories, graphs, and equations; relevant to students with various learning styles (verbal, visual, and numerical).

    This contemporary and student-relevant text gives you all the key material you need for your introductory course, plus it will show you that anthropology is for you! With real world applications of the principles and practices of anthropology, this book will help you learn to appreciate other cultures as well as your own. Apply what you learn in this course to those situations that you are likely to encounter in your personal and professional life. What can you do with anthropology today? Check out the real-life examples of cross-cultural misunderstandings and issues (in our popular "Cross-Cultural Miscues" features) to view 'culture at work.' Also, the book takes a look at specialized vocabularies as illustrated by "chickspeak" (the language of single, urban, upwardly mobile women), the war in Iraq, environmental degradation, and other contemporary topics.

    The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts which are set in abstract settings.