The science of complexity studies how single elements, such as a species or a stock, spontaneously organize into complicated structures like ecosystems and economies; stars become galaxies, and snowflakes avalanches almost as if these systems were obeying a hidden yearning for order. Drawing from diverse fields, scientific luminaries such as Nobel Laureates Murray Gell-Mann and Kenneth Arrow are studying complexity at a think tank called The Santa Fe Institute. The revolutionary new discoveries researchers have made there could change the face of every science from biology to cosmology to economics. M. Mitchell Waldrop's groundbreaking bestseller takes readers into the hearts and minds of these scientists to tell the story behind this scientific revolution as it unfolds.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    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.

    The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout. Author resource page: http: //www.stat.columbia.edu/ gelman/arm/

    As the recent collapse on Wall Street shows, we are often ill-equipped to deal with uncertainty and risk. Yet every day we base our personal and business plans on uncertainties, whether they be next month's sales, next year's costs, or tomorrow's stock price. In The Flaw of Averages, Sam Savage-known for his creative exposition of difficult subjects- describes common avoidable mistakes in assessing risk in the face of uncertainty. Along the way, he shows why plans based on average assumptions are wrong, on average, in areas as diverse as healthcare, accounting, the War on Terror, and climate change. In his chapter on Sex and the Central Limit Theorem, he bravely grasps the literary third rail of gender differences.Instead of statistical jargon, Savage presents complex concepts in plain English. In addition, a tightly integrated web site contains numerous animations and simulations to further connect the seat of the reader's intellect to the seat of their pants.The Flaw of Averages typically results when someone plugs a single number into a spreadsheet to represent an uncertain future quantity. Savage finishes the book with a discussion of the emerging field of Probability Management, which cures this problem though a new technology that can pack thousands of numbers into a single spreadsheet cell.Praise for The Flaw of Averages"Statistical uncertainties are pervasive in decisions we make every day in business, government, and our personal lives. Sam Savage's lively and engaging book gives any interested reader the insight and the tools to deal effectively with those uncertainties. I highly recommend The Flaw of Averages." --William J. Perry, Former U.S. Secretary of Defense"Enterprise analysis under uncertainty has long been an academic ideal. . . . In this profound and entertaining book, Professor Savage shows how to make all this practical, practicable, and comprehensible." ---Harry Markowitz, Nobel Laureate in Economics

    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

    As a celebrated cultural critic and a writer for national publications like The Atlantic and Harper's, Alan Jacobs has spent his adult life belonging to communities that often clash in America's culture wars. And in his years of confronting the big issues that divide us--political, social, religious--Jacobs has learned that many of our fiercest disputes occur not because we're doomed to be divided, but because the people involved simply aren't thinking.Most of us don't want to think, Jacobs writes. Thinking is trouble. Thinking can force us out of familiar, comforting habits, and it can complicate our relationships with like-minded friends. Finally, thinking is slow, and that's a problem when our habits of consuming information (mostly online) leave us lost in the spin cycle of social media, partisan bickering, and confirmation bias.In this smart, endlessly entertaining book, Jacobs diagnoses the many forces that act on us to prevent thinking--forces that have only worsened in the age of Twitter, "alternative facts," and information overload--and he also dispels the many myths we hold about what it means to think well. (For example: It's impossible to "think for yourself.")Drawing on sources as far-flung as novelist Marilynne Robinson, basketball legend Wilt Chamberlain, British philosopher John Stuart Mill, and Christian theologian C.S. Lewis, Jacobs digs into the nuts and bolts of the cognitive process, offering hope that each of us can reclaim our mental lives from the impediments that plague us all. Because if we can learn to think together, maybe we can learn to live together, too.

    In Standard Deviations, economics professor Gary Smith walks us through the various tricks and traps that people use to back up their own crackpot theories. Sometimes, the unscrupulous deliberately try to mislead us. Other times, the well-intentioned are blissfully unaware of the mischief they are committing. Today, data is so plentiful that researchers spend precious little time distinguishing between good, meaningful indicators and total rubbish. Not only do others use data to fool us, we fool ourselves.With the breakout success of Nate Silver’s The Signal and the Noise, the once humdrum subject of statistics has never been hotter. Drawing on breakthrough research in behavioral economics by luminaries like Daniel Kahneman and Dan Ariely and taking to task some of the conclusions of Freakonomics author Steven D. Levitt, Standard Deviations demystifies the science behind statistics and makes it easy to spot the fraud all around.

    Doctors, nurses, and clinicians swear by this code of conduct. Yet, medical errors are made every single day-avoidable mistakes that often cost lives. Inspired by two such mistakes, Dr. Peter Pronovost made it his personal mission to improve patient safety and make preventable deaths a thing of the past, one hospital at a time. Safe Patients, Smart Hospitals shows how Dr. Pronovost started a revolution by creating a simple checklist that standardized a common ICU procedure. His reforms are being implemented in all fifty states and have saved hundreds of lives by cutting hospital-acquired infection rates by 70%. Atul Gawande profiled Dr. Pronovost's reforms in a New Yorker article and his bestselling book The Checklist Manifesto is based upon Dr. Pronovost's success in patient safety. But Safe Patients, Smart Hospitals is the real story: an inspiring, thought-provoking, accessible insider's narrative about how doctors and nurses are improving patient care for all Americans, today.

    In the past, discoveries often had to wait for the rise of the next generation to see questions in a new light and let go of old truisms. Today, in a world that is defined by a rapid rate of change, staying on the cutting edge has as much to do with shedding outdated notions as adopting new ones. In this spirit, John Brockman, publisher of the online salon Edge.org ("the world's smartest website"—The Guardian), asked 175 of the world's most influential scientists, economists, artists, and philosophers: What scientific idea is ready for retirement?Jared Diamond explores the diverse ways that new ideas emerge * Nassim Nicholas Taleb takes down the standard deviation * Richard Thaler and novelist Ian McEwan reveal the usefulness of "bad" ideas * Steven Pinker dismantles the working theory of human behavior * Richard Dawkins renounces essentialism * Sherry Turkle reevaluates our expectations of artificial intelligence * Physicist Andrei Linde suggests that our universe and its laws may not be as unique as we think * Martin Rees explains why scientific understanding is a limitless goal * Alan Guth rethinks the origins of the universe * Sam Harris argues that our definition of science is too narrow * Nobel Prize winner Frank Wilczek disputes the division between mind and matter * Lawrence Krauss challenges the notion that the laws of physics were preordained * plus contributions from Daniel Goleman, Mihaly Csikszentmihalyi, Nicholas Carr, Rebecca Newberger Goldstein, Matt Ridley, Stewart Brand, Sean Carroll, Daniel C. Dennett, Helen Fisher, Douglas Rushkoff, Lee Smolin, Kevin Kelly, Freeman Dyson, and others.

    There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor M. G. Bulmer's Principles of Statistics, originally published in 1965, was created to fill that need. The new, corrected Dover edition of Principles of Statistics makes this invaluable mid-level text available once again for the classroom or for self-study.Principles of Statistics was created primarily for the student of natural sciences, the social scientist, the undergraduate mathematics student, or anyone familiar with the basics of mathematical language. It assumes no previous knowledge of statistics or probability; nor is extensive mathematical knowledge necessary beyond a familiarity with the fundamentals of differential and integral calculus. (The calculus is used primarily for ease of notation; skill in the techniques of integration is not necessary in order to understand the text.)Professor Bulmer devotes the first chapters to a concise, admirably clear description of basic terminology and fundamental statistical theory: abstract concepts of probability and their applications in dice games, Mendelian heredity, etc.; definitions and examples of discrete and continuous random variables; multivariate distributions and the descriptive tools used to delineate them; expected values; etc. The book then moves quickly to more advanced levels, as Professor Bulmer describes important distributions (binomial, Poisson, exponential, normal, etc.), tests of significance, statistical inference, point estimation, regression, and correlation. Dozens of exercises and problems appear at the end of various chapters, with answers provided at the back of the book. Also included are a number of statistical tables and selected references.

    Minimalist Budget will help you to turn your bloated expenses into a well-toned budget, spending on exactly what you need and nothing else. This book presents solutions for two major problems in our consumer society: (1) how to downsize your cravings without having to sacrifice the fun stuff, and (2) how to whip your finances into shape and follow a personalized budget. This is not a get rich quick book. But I can promise day-by-day, month-by-month, you’ll budget better and become richer as a consequence. Regardless of how much your income is we’ll find a way to budget, save, and increase your net worth. Since my youth, I’ve had to live on a budget that ranged from $100 to $200 a month if I was lucky. Even though I never knew how much I would have the next month, I was always able to have enough for my essential expenses, personal pleasures, and savings. If you’re tired of the false and impossible-to-follow promises of “finance gurus,” try out my simple, straightforward, easy-to-stick-to methods. Improve your spending habits: • Incorporate minimalism into your finances • How to avoid becoming a minimalist consumerist • Learn the psychological traps that make you overspend • Control your compulsive spending habits Feel financially secure every day: • Learn about two A-Z budgeting methods and how to make them work for you • Learn ratio-based budgeting and fixed-amount budgeting • Discover the best budgeting software programs • Design a bulletproof savings strategy to get out of debt, be prepared for emergencies, and set yourself up for retirement Stop hating your financial life: • Learn how to set SMART financial goals • Increase your self-confidence with budgeting • 50 small budgeting tips Financial education is not part of our educational system. It is normal that we don’t know how to budget when we step into the craziness we call adulthood. But it is not normal to stay ignorant about a field of life that (like it or not) guarantees our material survival. Money management is an essential skill for everybody who earns, shops or consumes. If you follow the budgeting tips in this book, you’ll be able to keep track of your finances. You’ll clearly know where your money goes, where it comes from and where can you save. You won’t feel stressed of running out of money unexpectedly, you’ll clear yourself out of debts and have savings for bigger expenses like a vacation, new car or unexpected events. Leave money struggles for yesterday. Grab a copy of Minimalist Budget by hitting buy now in the top right corner of this page.

    Human beings have long been both fascinated and appalled by randomness. On the one hand, we love the thrill of a surprise party, the unpredictability of a budding romance, or the freedom of not knowing what tomorrow will bring. We are inexplicably delighted by strange coincidences and striking similarities. But we also hate uncertainty's dark side. From cancer to SARS, diseases strike with no apparent pattern. Terrorists attack, airplanes crash, bridges collapse, and we never know if we'll be that one in a million statistic. We are all constantly faced with situations and choices that involve randomness and uncertainty. A basic understanding of the rules of probability theory, applied to real-life circumstances, can help us to make sense of these situations, to avoid unnecessary fear, to seize the opportunities that randomness presents to us, and to actually enjoy the uncertainties we face. The reality is that when it comes to randomness, you can run, but you can't hide. So many aspects of our lives are governed by events that are simply not in our control. In this entertaining yet sophisticated look at the world of probabilities, author Jeffrey Rosenthal--an improbably talented math professor--explains the mechanics of randomness and teaches us how to develop an informed perspective on probability.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

    This connectedness is found in many incarnations: in the rapid growth of the Internet, in the ease with which global communication takes place, and in the ability of news and information as well as epidemics and financial crises to spread with surprising speed and intensity. These are phenomena that involve networks, incentives, and the aggregate behavior of groups of people; they are based on the links that connect us and the ways in which our decisions can have subtle consequences for others. This introductory undergraduate textbook takes an interdisciplinary look at economics, sociology, computing and information science, and applied mathematics to understand networks and behavior. It describes the emerging field of study that is growing at the interface of these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected.