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Carregando... The Signal and the Noise: Why So Many Predictions Fail — but Some Don't (2012)de Nate Silver
  
Ainda não há conversas na Discussão sobre este livro.   ) zot79 | Aug 20, 2023 |  Nate Silver focuses on the forecasting in areas that are difficult to predict: weather, climate, earthquakes, poker, politics, chess and sports. Each of these areas is individually interesting -- I had never spent much time considering online poker, for instance, and the chapter focusing on poker is not just mathematically-focused, but also an expose on the world of online poker and the life and times (or at least the two year subset thereof) of Silver's 6-figure gambling career. In addition, his overall thesis, which seems to be that we should use Bayesian analysis to think probabilistically about the world and continually evaluate our probabilities both builds naturally and has far-reaching applications. I feel like I have spent years of my life trying to explain to medical students (and more advanced physicians who should really know better) why every time a paper is published with a p (  ) settingshadow | Aug 19, 2023 |  ) markm2315 | Jul 1, 2023 | The second half moves towards giving you an idea how to approach problems probabilistically and how to improve and refine your process over time. He starts with simple problems like sports and poker before moving onto more complex problems like terrorism and global warming. I wouldn’t consider this book a complete guide to rational, evidence based decision making (ignoring that it doesn’t give you the math), but it’s a pretty accessible introduction to the topic and is largely technically sound. It’s a solid place to start. ( ) jdm9970 | Jan 26, 2023 | ) steve02476 | Jan 3, 2023 |
 The first thing to note about The Signal and the Noise is that it is modest – not lacking in confidence or pointlessly self-effacing, but calm and honest about the limits to what the author or anyone else can know about what is going to happen next. Across a wide range of subjects about which people make professional predictions – the housing market, the stock market, elections, baseball, the weather, earthquakes, terrorist attacks – Silver argues for a sharper recognition of "the difference between what we know and what we think we know" and recommends a strategy for closing the gap.  What Silver is doing here is playing the role of public statistician — bringing simple but powerful empirical methods to bear on a controversial policy question, and making the results accessible to anyone with a high-school level of numeracy. The exercise is 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. Except that their authority was based to varying degrees on their establishment credentials, whereas Silver’s derives from his data savvy in the age of the stats nerd.  A friend who was a pioneer in the computer games business used to marvel at how her company handled its projections of costs and revenue. “We performed exhaustive calculations, analyses and revisions,” she would tell me. “And we somehow always ended with numbers that justified our hiring the people and producing the games we had wanted to all along.” Those forecasts rarely proved accurate, but as long as the games were reasonably profitable, she said, you’d keep your job and get to create more unfounded projections for the next endeavor....... In the course of this entertaining popularization of a subject that scares many people off, the signal of Silver’s own thesis tends to get a bit lost in the noise of storytelling. The asides and digressions are sometimes delightful, as in a chapter about the author’s brief adventures as a professional poker player, and sometimes annoying, as in some half-baked musings on the politics of climate change. But they distract from Silver’s core point: For all that modern technology has enhanced our computational abilities, there are still an awful lot of ways for predictions to go wrong thanks to bad incentives and bad methods. Mr. Silver reminds us that we live in an era of "Big Data," with "2.5 quintillion bytes" generated each day. But he strongly disagrees with the view that the sheer volume of data will make predicting easier. "Numbers don't speak for themselves," he notes. In fact, we imbue numbers with meaning, depending on our approach. We often find patterns that are simply random noise, and many of our predictions fail: "Unless we become aware of the biases we introduce, the returns to additional information may be minimal—or diminishing." The trick is to extract the correct signal from the noisy data. "The signal is the truth," Mr. Silver writes. "The noise is the distraction." PrêmiosDistinctionsNotable Lists
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. Drawing on his own groundbreaking work, Silver examines the world of prediction. Não foram encontradas descrições de bibliotecas. |
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 Google Books — Carregando...GênerosClassificação decimal de Dewey (CDD)519.5Natural sciences and mathematics Mathematics Applied Mathematics, Probabilities Statistical MathematicsClassificação da Biblioteca do Congresso dos E.U.A. (LCC)AvaliaçãoMédia: (3.83)
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