With boundless erudition and in delightfully clear prose, Surowiecki ranges across fields as diverse as popular culture, psychology, ant biology, behavioral economics, artificial intelligence, military history, and politics to show how this simple idea offers important lessons for how we live our lives, select our leaders, run our companies, and think about our world.

    It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.

    It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable. Professor of Computer Science at the UCLA, Judea Pearl is the winner of the 2008 Benjamin Franklin Award in Computers and Cognitive Science.

    With this book, you'll learn how to load data, assemble and disassemble data objects, navigate R's environment system, write your own functions, and use all of R's programming tools.RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You'll gain valuable programming skills and support your work as a data scientist at the same time.Work hands-on with three practical data analysis projects based on casino gamesStore, retrieve, and change data values in your computer's memoryWrite programs and simulations that outperform those written by typical R usersUse R programming tools such as if else statements, for loops, and S3 classesLearn how to write lightning-fast vectorized R codeTake advantage of R's package system and debugging toolsPractice and apply R programming concepts as you learn them

    It can be freely downloaded and it works on multiple computer platforms. This book provides an elementary introduction to R. In each chapter, brief introductory sections are followed by code examples and comments from the computational and statistical viewpoint. A supplementary R package containing the datasets can be downloaded from the web.

    Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions.Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more.Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech-savvy businesses Helps readers see how to shepherd predictive analytics projects through their companies Explains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and more Covers nuts-and-bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing data Also covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewhere Propose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies.

    But all too often, even the most respected publications present numbers that are miscalculated, misinterpreted, hyped, or simply misleading. Following on the heels of his highly acclaimed Damned Lies and Statistics and More Damned Lies and Statistics, Joel Best now offers this practical field guide to help everyone identify questionable statistics. Entertaining, informative, and concise, Stat-Spotting is essential reading for people who want to be more savvy and critical consumers of news and information.Stat-Spotting features:* Pertinent examples from today's news, including the number of deaths reported in Iraq, the threat of secondhand smoke, the increase in the number of overweight Americans, and many more* A commonsense approach that doesn't require advanced math or statistics

    Scientists have marveled at the beauty and elegance of his analysis, while ordinary programmers have successfully applied his "cookbook" solutions to their day-to-day problems. All have admired Knuth for the breadth, clarity, accuracy, and good humor found in his books. "I can't begin to tell you how many pleasurable hours of study and recreation they have afforded me I have pored over them in cars, restaurants, at work, at home... and even at a Little League game when my son wasn't in the line-up.""--"Charles Long Primarily written as a reference, some people have nevertheless found it possible and interesting to read each volume from beginning to end. A programmer in China even compared the experience to reading a poem. "If you think you're a really good programmer... read Knuth's] "Art of Computer Programming.".. You should definitely send me a resume if you can read the whole thing.""--"Bill Gates Whatever your background, if you need to do any serious computer programming, you will find your own good reason to make each volume in this series a readily accessible part of your scholarly or professional library. "It's always a pleasure when a problem is hard enough that you have to get the Knuths off the shelf. I find that merely opening one has a very useful terrorizing effect on computers.""--"Jonathan LaventholIn describing the new fourth volume, one reviewer listed the qualities that distinguish all of Knuth's work. In sum: ] "detailed coverage of the basics, illustrated with well-chosen examples; occasional forays into more esoteric topics and problems at the frontiers of research; impeccable writing peppered with occasional bits of humor; extensive collections of exercises, all with solutions or helpful hints; a careful attention to history; implementations of many of the algorithms in his classic step-by-step form."--Frank RuskeyThese four books comprise what easily could be the most important set of information on any serious programmer's bookshelf.

    Employing a methodology that is primarily learning by example and “thinking with our eyes,” this manual features graphs and practical analytical techniques that can be applied to a broad range of data analysis tools—including the most commonly used Microsoft Excel. This approach is particularly valuable to those who need to make sense of quantitative business data by discerning meaningful patterns, trends, relationships, and exceptions that reveal business performance, potential problems and opportunities, and hints about the future. It provides practical skills that are useful to managers at all levels and to those interested in keeping a keen eye on their business.

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

    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.

    This friendly, easy-to-read guide gently introduces you to the most commonly used features of SAS software plus a whole lot more! Authors Lora Delwiche and Susan Slaughter have revised the text to include concepts of the Output Delivery System; the STYLE= option in the PRINT, REPORT, and TABULATE procedures; ODS HTML, RTF, PRINTER, and OUTPUT destinations; PROC REPORT; more on PROC TABULATE; exporting data; and the colon modifier for informats. You'll find clear and concise explanations of basic SAS concepts (such as DATA and PROC steps), inputting data, modifying and combining data sets, summarizing and presenting data, basic statistical procedures, and debugging SAS programs. Each topic is presented in a self-contained, two-page layout complete with examples and graphics. This format enables new users to get up and running quickly, while the examples allow you to type in the program and see it work!

    This updated edition of Ross's classic bestseller provides an introduction to elementary probability theory and stochastic processes, and shows how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. With the addition of several new sections relating to actuaries, this text is highly recommended by the Society of Actuaries.This book now contains a new section on compound random variables that can be used to establish a recursive formula for computing probability mass functions for a variety of common compounding distributions; a new section on hiddden Markov chains, including the forward and backward approaches for computing the joint probability mass function of the signals, as well as the Viterbi algorithm for determining the most likely sequence of states; and a simplified approach for analyzing nonhomogeneous Poisson processes. There are also additional results on queues relating to the conditional distribution of the number found by an M/M/1 arrival who spends a time t in the system; inspection paradox for M/M/1 queues; and M/G/1 queue with server breakdown. Furthermore, the book includes new examples and exercises, along with compulsory material for new Exam 3 of the Society of Actuaries.This book is essential reading for professionals and students in actuarial science, engineering, operations research, and other fields in applied probability.

    Introductory Graph Theory presents a nontechnical introduction to this exciting field in a clear, lively, and informative style. Author Gary Chartrand covers the important elementary topics of graph theory and its applications. In addition, he presents a large variety of proofs designed to strengthen mathematical techniques and offers challenging opportunities to have fun with mathematics. Ten major topics — profusely illustrated — include: Mathematical Models, Elementary Concepts of Graph Theory, Transportation Problems, Connection Problems, Party Problems, Digraphs and Mathematical Models, Games and Puzzles, Graphs and Social Psychology, Planar Graphs and Coloring Problems, and Graphs and Other Mathematics. A useful Appendix covers Sets, Relations, Functions, and Proofs, and a section devoted to exercises — with answers, hints, and solutions — is especially valuable to anyone encountering graph theory for the first time. Undergraduate mathematics students at every level, puzzlists, and mathematical hobbyists will find well-organized coverage of the fundamentals of graph theory in this highly readable and thoroughly enjoyable book.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates