We consistently look to the experts - full-time faculty members, adjunct instructors, and of course students - to drive the decisions we make about the text itself and the ancillary package. Through a series of focus groups, symposia, as well as full-book, single-chapter, revised manuscript reviews of both text and key ancillaries, we have heard the stories of more than 500 professors and their insights and experiences are evident on every page of the revision and in every supplement. As teachers of the course and users of their own materials, the author team is dedicated to the principles of excellence in business education. pedagogy that puts students in touch with today's real business issues, to creating groundbreaking and market-defining ancillary items for professors and students alike, Understanding Business leads the way.

    The text begins with a discussion of the real number system as a complete ordered field. (Dedekind's construction is now treated in an appendix to Chapter I.) The topological background needed for the development of convergence, continuity, differentiation and integration is provided in Chapter 2. There is a new section on the gamma function, and many new and interesting exercises are included. This text is part of the Walter Rudin Student Series in Advanced Mathematics.

    Clear explanations are detailed with many current examples.

    It is the standard work in the field. The text covers learning about children s literature, understanding children s responses to literature, the history of children s literature, beginning books, picture books and all of the genres (fantasy, poetry, realistic fiction, historical fiction, biography, and informational books), planning the literature program, and extending and evaluating children s understandings of literature."

    Robert Gibbons addresses scholars in applied fields within economics who want a serious and thorough discussion of game theory but who may have found other works overly abstract. Gibbons emphasizes the economic applications of the theory at least as much as the pure theory itself; formal arguments about abstract games play a minor role. The applications illustrate the process of model building--of translating an informal description of a multi-person decision situation into a formal game-theoretic problem to be analyzed. Also, the variety of applications shows that similar issues arise in different areas of economics, and that the same game-theoretic tools can be applied in each setting. In order to emphasize the broad potential scope of the theory, conventional applications from industrial organization have been largely replaced by applications from labor, macro, and other applied fields in economics. The book covers four classes of games, and four corresponding notions of equilibrium: static games of complete information and Nash equilibrium, dynamic games of complete information and subgame-perfect Nash equilibrium, static games of incomplete information and Bayesian Nash equilibrium, and dynamic games of incomplete information and perfect Bayesian equilibrium.

    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.

    This edition is thoroughly revised, now including more application and analysis problems.

    Fully revised to meet the needs of the wide range of students beginning engineering courses, this edition has an extended Foundation section including new chapters on graphs, trigonometry, binomial series and functions and a CD-ROM

    Full of insights, arguments and philosophical perspectives, the book covers an amazing array of topics. Beginning in antiquity with Democritus, it progresses through logic and set theory, computability and complexity theory, quantum computing, cryptography, the information content of quantum states and the interpretation of quantum mechanics. There are also extended discussions about time travel, Newcomb's Paradox, the anthropic principle and the views of Roger Penrose. Aaronson's informal style makes this fascinating book accessible to readers with scientific backgrounds, as well as students and researchers working in physics, computer science, mathematics and philosophy.

    Integrated MLA 2003 update

    People are predictable even when they try not to be. William Poundstone demonstrates how to turn this fact to personal advantage in scores of everyday situations, from playing the lottery to buying a home. Rock Breaks Scissors is mind-reading for real life. Will the next tennis serve go right or left? Will the market go up or down? Most people are poor at that kind of predicting. We are hard-wired to make bum bets on "trends" and "winning streaks" that are illusions. Yet ultimately we're all in the business of anticipating the actions of others. Poundstone reveals how to overcome the errors and improve the accuracy of your own outguessing. Rock Breaks Scissors is a hands-on guide to turning life's odds in your favor.