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Loading... The signal and the noise: Why so many predictions fail—but some don'tby Nate Silver
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No current Talk conversations about this book. Mostly excellent tour of different disciplines where predictions are made -- from natural disasters to financial markets to sports to politics. Silver makes a strong case for using Bayesian reasoning whenever possible, and encourages fox-like thinking vs. hedgehog thinking -- hence the fox icon on the fivethirtyeight website. In his chapter on political pundits, Silver skewers Dick Morris for having predicted that Donald Trump would mount a credible campaign for the presidency in 2012. It turns out he was only off by one election cycle! A fairly heavy read, but provides insight into how data can be used correctly or incorrectly to support an idea or a theory. Math geeks will love this one. Disorganized a bit too heavy for my tastes. A very disappointing book for anyone who knows anything about statistics, probability and forecasting.
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."
References to this work on external resources.
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If I have one complaint about this book, it's that there is almost too much of a good thing. What he's saying is great, well-expressed, and very much worth saying, and his examples are good, but there are so many of them, and he discusses them so thoroughly, that by the end my brain was getting a little tired. Then again, maybe that's my fault as much as Silver's, as one thing I did notice is that my level of brain fatigue depended a lot in my own interest levels in whatever area he was currently considering. Attempts to predict natural disasters or terrorist attacks, or to sort the noise of weather from the signal of climate? Fairly exciting stuff to me, and I zipped through it. But economics makes my eyes glaze over and baseball makes me yawn, and there was an awful lot of both.
Still. I definitely recommend it to anyone who is willing to take a bit of a dive into this subject, whether or not you happen t be a baseball fan. Although you'll probably enjoy parts of it much more than I did if you are. (