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.

    In a series of startling experiments, Canadian scientist Dr. John Coates identified a feedback loop between testosterone and success that dramatically lowers the fear of risk in men, especially young men; he has vividly dubbed the moment when traders transform into exuberant high flyers "the hour between dog and wolf." Similarly, intense failure leads to a rise in levels of cortisol, which dramatically lowers the appetite for risk. His book expands on his seminal research to offer lessons from the exploding new field studying the biology of risk. Coates's conclusions shed light on all types of high-pressure decision-making, from the sports field to the battlefield, and leaves us with a powerful recognition: to handle risk isn't a matter of mind over body, it's a matter of mind and body working together. We all have it in us to be transformed from dog to wolf; the only question is whether we can understand the causes and the consequences.

    The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text.

    But, with Max Bazerman's Judgment in Managerial Decision Making, Sixth Edition, you can learn how to overcome those biases to make better managerial decisions. The text examines judgment in a variety of organizational contexts, and provides practical strategies for changing your decision-making processes and improving these processes so that they become part of your permanent behavior. Throughout, you'll findnumerous hands-on decision exercises and examples from the author's extensive executive training experience that will help you enhance the quality of your managerial judgment. Past editions have been used in top universities, in business schools, and in public policy, psychology, and economics classes. In addition, the text has been widely recognized by practitioners in the world of behavioral finance. Revised with two new chapters This Sixth Edition now adds chapters on bounded ethicality (Chapter 8) and bounded awareness (Chapter 11). Both of these chapters are based on Bazerman's recent writing with Dolly Chugh and Mahzarin Banaji. Max H. Bazerman is the Jesse Isidor Straus Professor of Business Administration at the Harvard Business School. In addition, Max is also formally affiliated with the Kennedy School of Government, the Psychology Department, and the Program on Negotiation at Harvard. He is the author or co-author of over 150 research articles and chapters, and the author of numerous other books. Max was named one of the top 30 authors, speakers, and teachers of management by Executive Excellence in each of their two most recent rankings.

    In How Not to Be Wrong, Jordan Ellenberg shows us how terribly limiting this view is: Math isn’t confined to abstract incidents that never occur in real life, but rather touches everything we do—the whole world is shot through with it.Math allows us to see the hidden structures underneath the messy and chaotic surface of our world. It’s a science of not being wrong, hammered out by centuries of hard work and argument. Armed with the tools of mathematics, we can see through to the true meaning of information we take for granted: How early should you get to the airport? What does “public opinion” really represent? Why do tall parents have shorter children? Who really won Florida in 2000? And how likely are you, really, to develop cancer?How Not to Be Wrong presents the surprising revelations behind all of these questions and many more, using the mathematician’s method of analyzing life and exposing the hard-won insights of the academic community to the layman—minus the jargon. Ellenberg chases mathematical threads through a vast range of time and space, from the everyday to the cosmic, encountering, among other things, baseball, Reaganomics, daring lottery schemes, Voltaire, the replicability crisis in psychology, Italian Renaissance painting, artificial languages, the development of non-Euclidean geometry, the coming obesity apocalypse, Antonin Scalia’s views on crime and punishment, the psychology of slime molds, what Facebook can and can’t figure out about you, and the existence of God.Ellenberg pulls from history as well as from the latest theoretical developments to provide those not trained in math with the knowledge they need. Math, as Ellenberg says, is “an atomic-powered prosthesis that you attach to your common sense, vastly multiplying its reach and strength.” With the tools of mathematics in hand, you can understand the world in a deeper, more meaningful way. How Not to Be Wrong will show you how.

    This book leads the reader from simple graphs through planar graphs, Euler's formula, Platonic graphs, coloring, the genus of a graph, Euler walks, Hamilton walks, more. Includes exercises. 1976 edition.

    Explaining why the whole is sometimes smarter than the sum of its parts, Johnson presents surprising examples of feedback, self-organization, and adaptive learning. How does a lively neighborhood evolve out of a disconnected group of shopkeepers, bartenders, and real estate developers? How does a media event take on a life of its own? How will new software programs create an intelligent World Wide Web? In the coming years, the power of self-organization -- coupled with the connective technology of the Internet -- will usher in a revolution every bit as significant as the introduction of electricity. Provocative and engaging, Emergence puts you on the front lines of this exciting upheaval in science and thought.

    Based on Knight's PhD dissertation, this 1921 work, balancing theory with fact to come to stunning insights, is a distinct pleasure to read. FRANK H. KNIGHT (1885-1972) is considered by some the greatest American scholar of economics of the 20th century. An economics professor at the University of Chicago from 1927 until 1955, he was one of the founders of the Chicago school of economics, which influenced Milton Friedman and George Stigler.

    From Simon & Schuster, This Book Needs No Title is Raymond Smullyan's budget of living paradoxes—the author of What is the Name of This Book?Including eighty paradoxes, logical labyrinths, and intriguing enigmas progress from light fables and fancies to challenging Zen exercises and a novella and probe the timeless questions of philosophy and life.

    The McDonaldization of Society, Revised New Century Edition discusses how McDonaldization and the broader process of globalization (in a new Chapter 8), are spreading more widely and more deeply into various social institutions such as education, medicine, the criminal justice system, and more. This Revised New Century Edition provides many new, relevant examples from recent events and contemporary popular culture, including the ever-increasing global proliferation of McDonald′s and other fast food franchises, shopping malls, and similar commercial entities. Their impact is examined in the post-September 11, 2001 era.

    It is designed as a reference for students in the physical sciences and engineering.

    The reliance traders put on such quantitative analysis was catastrophic for the economy, setting off the series of financial crises that began to erupt in 2007 with the mortgage crisis and from which we're still recovering. Here Derman looks at why people--bankers in particular--still put so much faith in these models, and why it's a terrible mistake to do so.Though financial models imitate the style of physics by using the language of mathematics, ultimately they deal with human beings. Their similarity confuses the fundamental difference between the aims and possible achievements of the phsyics world and that of the financial world. When we make a model involving human beings, we are trying to force the ugly stepsister's foot into Cinderella's pretty glass slipper.  It doesn't fit without cutting off some of the essential parts. Physicists and economists have been too enthusiastic to recognize the limits of their equations in the sphere of human behavior--which of course is what economics is all about.  Models.Behaving.Badly. includes a personal account Derman's childhood encounter with failed models--the utopia of the kibbutz, his experience as a physicist on Wall Street, and a look at the models quants generated: the benefits they brought and the problems they caused. Derman takes a close look at what a model is, and then he highlights the differences between the success of modeling in physics and its relative failure in economics.  Describing the collapse of the subprime mortgage CDO market in 2007, Derman urges us to stop relying on these models where possible, and offers suggestions for mending these models where they might still do some good.  This is a fascinating, lyrical, and very human look behind the curtain at the intersection between mathematics and human nature.

    The 17th Edition builds upon the tradition of leadership by sticking to 3 main goals: help the beginning student master the principles essential for understanding the economizing problem, specific economic issues, and the policy alternatives; help the student understand and apply the economic perspective and reason accurately and objectively about economic matters; and promote a lasting student interest in economics and the economy.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    Paradoxically, just as such demands seem as elusive as ever at a political level, they are becoming encoded into the very technological foundations of neoliberalism. Srnicek examines technologies such as automated logistics, cybernetic planning, and additive manufacturing in order to re-interpret older debates about worker control over the means of production, the 'fetters' of capitalist development, and situationist concepts of détournement. In so doing, the foundations and future of neoliberalism are brought under intense scrutiny.