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Bayes rule appears to be a straightforward, one-line theorem: by updating our initial beliefs with objective new information, we get a new and improved belief. To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok. In the first-ever account of Bayes' rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the human obsessions surrounding it. She traces its discovery by an amateur mathematician in the 1740s through its development into roughly its modern form by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years at the same time that practitioners relied on it to solve crises involving great uncertainty and scanty information, even breaking Germany's Enigma code during World War II, and explains how the advent of off-the-shelf computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA de-coding to Homeland Security.Drawing on primary source material and interviews with statisticians and other scientists, The Theory That Would Not Die is the riveting account of how a seemingly simple theorem ignited one of the greatest controversies of all time.
In today’s fast-paced and global workplace, project management takes on new meaning. Virtual meetings, portable technology, and tighter budgets add to the risk of project failure. Yet businesses must continue forward with new products or services, meet demands, and market their goods. These goals depend on effective project management. When project management fails, businesses often follow. Project Management Made Simple and Effective teaches you the principles of successful project management so you can adapt to this environment. You’ll learn different techniques for leading project teams and getting the attention of busy executives. You’ll also learn how to avoid common problems that can create havoc with the most experienced project teams. Applying a Portfolio Approach Managing Stakeholders Defining Scope Identifying the Critical Path Measuring Status of the Schedule, Scope, and Budget Resolving Conflicts that Occur During a Project The author and contributors also share useful, easy-to-use templates that may be downloaded from their website. Whether you’re an experienced Project Manager or someone leading their first work team, Project Management Made Simple and Effective gives you the practical tools, insights, and advice to be successful project managers.
Although there are countless books on statistics, few are dedicated to the application of statistical methods to software engineering. Simple Statistical Methods for Software Engineering: Data and Patterns fills that void. Instead of delving into overly complex statistics, the book details simpler solutions that are just as effective and connect with the intuition of problem solvers. Sharing valuable insights into software engineering problems and solutions, the book not only explains the required statistical methods, but also provides many examples, review questions, and case studies that provide the understanding required to apply those methods to real-world problems. After reading this book, practitioners will possess the confidence and understanding to solve day-to-day problems in quality, measurement, performance, and benchmarking. By following the examples and case studies, students will be better prepared able to achieve seamless transition from academic study to industry practices. Includes boxed stories, case studies, and illustrations that demonstrate the nuances behind proper application Supplies historical anecdotes and traces statistical methods to inventors and gurus Applies basic statistical laws in their simplest forms to resolve engineering problems Provides simple techniques for addressing the issues software engineers face The book starts off by reviewing the essential facts about data. Next, it supplies a detailed review and summary of metrics, including development, maintenance, test, and agile metrics. The third section covers the fundamental laws of probability and statistics and the final section presents special data patterns in the form of tailed mathematical distributions. In addition to selecting simpler and more flexible tools, the authors have also simplified several standard techniques to provide you with the set of intellectual tools all software engineers and managers require.
One of Wall Street Journal's Best Ten Works of Nonfiction in 2012 New York Times Bestseller “Not so different in spirit from the way public intellectuals like John Kenneth Galbraith once shaped discussions of economic policy and public figures like Walter Cronkite helped sway opinion on the Vietnam War…could turn out to be one of the more momentous books of the decade.” —New York Times Book Review "Nate Silver's The Signal and the Noise is The Soul of a New Machine for the 21st century." —Rachel Maddow, author of Drift "A serious treatise about the craft of prediction—without academic mathematics—cheerily aimed at lay readers. Silver's coverage is polymathic, ranging from poker and earthquakes to climate change and terrorism." —New York Review of Books Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger—all by the time he was thirty. He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of the website FiveThirtyEight. Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the “prediction paradox”: The more humility we have about our ability to make predictions, the more successful we can be in planning for the future. In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball, from the poker table to the stock market, from Capitol Hill to the NBA. He explains and evaluates how these forecasters think and what bonds they share. What lies behind their success? Are they good—or just lucky? What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary—and dangerous—science. Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise. With everything from the health of the global economy to our ability to fight terrorism dependent on the quality of our predictions, Nate Silver’s insights are an essential read.
Did Jesus rise physically from the dead, or did he rise as a real, non-bodily apparition, like those reported in the parapsychological literature? In this book, which is the first book-length examination of the question in over fifty years, Jake O'Connell argues in favor of the physical resurrection hypothesis. In order to do so, he employs Bayes' Theorem, a mathematical theorem which encapsulates the way humans think when they analyze the probability of a hypothesis. In addition, he provides a thorough overview of the evidence for the reality of apparitions of the dead.
As we use the Web for social networking, shopping, and news, we leave a personal trail. These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion. These are just basic examples of the growth of "Web intelligence", as increasingly sophisticated algorithms operate on the vast and growing amount of data on the Web, sifting, selecting, comparing, aggregating, correcting; following simple but powerful rules to decide what matters. While original optimism for Artificial Intelligence declined, this new kind of machine intelligence is emerging as the Web grows ever larger and more interconnected. Gautam Shroff takes us on a journey through the computer science of search, natural language, text mining, machine learning, swarm computing, and semantic reasoning, from Watson to self-driving cars. This machine intelligence may even mimic at a basic level what happens in the brain.
In the vein of A Beautiful Mind, The Man Who Loved Only Numbers, and Rosalind Franklin: The Dark Lady of DNA, this volume tells the poignant story of the brilliant, colorful, controversial mathematician named Dorothy Wrinch. Drawing on her own personal and professional relationship with Wrinch and archives in the United States, Canada, and England, Marjorie Senechal explores the life and work of this provocative, scintillating mind. Senechal portrays a woman who was learned, restless, imperious, exacting, critical, witty, and kind. A young disciple of Bertrand Russell while at Cambridge, the first women to receive a doctor of science degree from Oxford University, Wrinch's contributions to mathematical physics, philosophy, probability theory, genetics, protein structure, and crystallography were anything but inconsequential. But Wrinch, a complicated and ultimately tragic figure, is remembered today for her much publicized feud with Linus Pauling over the molecular architecture of proteins. Pauling ultimately won that bitter battle. Yet, Senechal reminds us, some of the giants of mid-century science--including Niels Bohr, Irving Langmuir, D'Arcy Thompson, Harold Urey, and David Harker--took Wrinch's side in the feud. What accounts for her vast if now-forgotten influence? What did these renowned thinkers, in such different fields, hope her model might explain? Senechal presents a sympathetic portrait of the life and work of a luminous but tragically flawed character. At the same time, she illuminates the subtler prejudices Wrinch faced as a feisty woman, profound culture clashes between scientific disciplines, ever-changing notions of symmetry and pattern in science, and the puzzling roles of beauty and truth.

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