No matter your interests (sports, movies, politics), your industry (finance, marketing, technology, manufacturing), or the type of organization you work for (big company, nonprofit, small start-up)—your world is awash with data.As a successful manager today, you must be able to make sense of all this information. You need to be conversant with analytical terminology and methods and able to work with quantitative information. This book promises to become your �quantitative literacy" guide—helping you develop the analytical skills you need right now in order to summarize data, find the meaning in it, and extract its value.In Keeping Up with the Quants, authors, professors, and analytics experts Thomas Davenport and Jinho Kim offer practical tools to improve your understanding of data analytics and enhance your thinking and decision making. You’ll gain crucial skills, including:� How to formulate a hypothesis� How to gather and analyze relevant data� How to interpret and communicate analytical results� How to develop habits of quantitative thinking� How to deal effectively with the �quants” in your organizationBig data and the analytics based on it promise to change virtually every industry and business function over the next decade. If you don’t have a business degree or if you aren’t comfortable with statistics and quantitative methods, this book is for you. Keeping Up with the Quants will give you the skills you need to master this new challenge—and gain a significant competitive edge.

    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.

    The book also contains a 10-page interview with Pratchett titled Discworld Quo Vadis?.

    With many lives and millions of pounds at stake, the race is on to solve the mystery of the terrifying Trojan virus.

    This process of “self-organization” reveals itself in the inanimate worlds of crystals and seashells, but as Len Fisher shows, it is also evident in living organisms, from fish to ants to human beings. The coordinated movements of fish in shoals, for example, arise from the simple rule: “Follow the fish in front.” Traffic flow arises from simple rules: “Keep your distance” and “Keep to the right.”Now, in his new book, Fisher shows how we can manage our complex social lives in an ever more chaotic world. His investigation encompasses topics ranging from “swarm intelligence” to the science of parties and the best ways to start a fad. Finally, Fisher sheds light on the beauty and utility of complexity theory. An entertaining journey into the science of everyday life, The Perfect Swarm will delight anyone who wants to understand the complex situations in which we so often find ourselves.

    Extraterrestrials ... Our genetic destiny ... The roots of language and learning ... Quantum physics and the shape of the universe ... Artificial intelligence .. In a masterful "trial by reason," author John L. Casti presents all sides of the most important and vital scientific debates raging in the world today -- scrutinizing six perplexing "great questions" in the most engaging, astonishing and accessible amalgam of science and literature since "A Brief History of Time.

    With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.Use graphics to describe data with one, two, or dozens of variablesDevelop conceptual models using back-of-the-envelope calculations, as well asscaling and probability argumentsMine data with computationally intensive methods such as simulation and clusteringMake your conclusions understandable through reports, dashboards, and other metrics programsUnderstand financial calculations, including the time-value of moneyUse dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situationsBecome familiar with different open source programming environments for data analysisFinally, a concise reference for understanding how to conquer piles of data.--Austin King, Senior Web Developer, MozillaAn indispensable text for aspiring data scientists.--Michael E. Driscoll, CEO/Founder, Dataspora

    The authors provide precise definitions and full proofs of results, sacrificing generalities and limiting the scope of the material in order to do so. The text is organized in four parts: strategic games, extensive games with perfect information, extensive games with imperfect information, and coalitional games. It includes over 100 exercises. Solution ManualTable of Contents, Errata, and more...

    CONTAINS MCQ'S

    The salient features of the book are as follows: It exactly covers the prescribed syllabus. Nothing undesirable has been included and nothing essential has been left. Its approach is explanatory and language is lucid and communicable. The exposition of the subject matter is systematic and the students are better prepared to solve the problems. All fundamentals of the included topics are explained with a micro-analysis. Sufficient number of solved examples have been given to let the students understand the various skills necessary to solve the problems. These examples are well-graded. Unsolved exercises of multi-varieties have been given in a well-graded style. Attempting those on his own, will enable a student to create confidence and independence in him/her regarding the understanding of the subject. Daily life problems and practical applications have been incorporated in the body of the text. A large number of attractive and accurate figures have been drawn which enable a student to grasp the subject in an easier way. All the answers have been checked and verified. About The Author: N.P. Bali is a prolific author of over 100 books for degree and engineering students. He has been writing books for more than forty years. His books on the following topics are well known for their easy comprehension and lucid presentation: Algebra, Trigonometry, Differential Calculus, Integral Calculus, Real Analysis, Co-ordinate Geometry, Statics, Dynamics etc. Dr. Manish Goyal has been associated with

    Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.

    Included are step-by-step instructions on how to carry out Bayesian data analyses.Download Link : readbux.com/download?i=0124058884            0124058884 Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan PDF by John Kruschke

    Epstein and Robert L. Axtell approach this age-old question with cutting-edge computer simulation techniques. Such fundamental collective behaviors as group formation, cultural transmission, combat, and trade are seen to "emerge" from the interaction of individual agents following simple local rules.In their computer model, Epstein and Axtell begin the development of a "bottom up" social science. Their program, named Sugarscape, simulates the behavior of artificial people (agents) located on a landscape of a generalized resource (sugar). Agents are born onto the Sugarscape with a vision, a metabolism, a speed, and other genetic attributes. Their movement is governed by a simple local rule: "look around as far as you can; find the spot with the most sugar; go there and eat the sugar." Every time an agent moves, it burns sugar at an amount equal to its metabolic rate. Agents die if and when they burn up all their sugar. A remarkable range of social phenomena emerge. For example, when seasons are introduced, migration and hibernation can be observed. Agents are accumulating sugar at all times, so there is always a distribution of wealth.Next, Epstein and Axtell attempt to grow a "proto-history" of civilization. It starts with agents scattered about a twin-peaked landscape; over time, there is self-organization into spatially segregated and culturally distinct "tribes" centered on the peaks of the Sugarscape. Population growth forces each tribe to disperse into the sugar lowlands between the mountains. There, the two tribes interact, engaging in combat and competing for cultural dominance, to produce complex social histories with violent expansionist phases, peaceful periods, and so on. The proto-history combines a number of ingredients, each of which generates insights of its own. One of these ingredients is sexual reproduction. In some runs, the population becomes thin, birth rates fall, and the population can crash. Alternatively, the agents may over-populate their environment, driving it into ecological collapse.When Epstein and Axtell introduce a second resource (spice) to the Sugarscape and allow the agents to trade, an economic market emerges. The introduction of pollution resulting from resource-mining permits the study of economic markets in the presence of environmental factors.This study is part of the 2050 Project, a joint venture of the Santa Fe Institute, the World Resources Institute, and the Brookings Institution. The project is an international effort to identify conditions for a sustainable global system in the middle of the next century and to design policy actions to help achieve such a system.

    Suitable for a two semester course in complex analysis, or as a supplementary text for an advanced course in function theory, this book aims to give students a good foundation of complex analysis and provides a basis for solving problems in mathematics, physics, engineering and many other sciences.

    Developed for the professional Master's program in Computational Finance at Carnegie Mellon, the leading financial engineering program in the U.S.Has been tested in the classroom and revised over a period of several yearsExercises conclude every chapter; some of these extend the theory while others are drawn from practical problems in quantitative finance