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The signal and the noise : why most…
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The signal and the noise : why most predictions fail but some don't (edition 2012)

by Nate Silver

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965None8,933 (3.97)20
Member:ansate
Title:The signal and the noise : why most predictions fail but some don't
Authors:Nate Silver
Info:New York : Penguin Press, 2012.
Collections:Read but unowned
Rating:***
Tags:nonfiction, statistics, library

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The Signal and the Noise: Why So Many Predictions Fail — but Some Don't by Nate Silver

Recently added byZiggaroth, krishami, private library, pa5t0rd, nthsSeniorCamp, efreibauer, MonkeyRobo, TrueNorth
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  1. 10
    Thinking, Fast and Slow by Daniel Kahneman (BenTreat)
    BenTreat: Integrates some of the analytical techniques Silver describes with common irrational patterns of decision-making; Kahneman's book explains how to use some of Silver's techniques (and other tools) to avoid making decisions which are not in one's own best interest.… (more)
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English (35)  German (1)  Danish (1)  All languages (37)
Showing 1-5 of 35 (next | show all)
Among the best non-fiction i've read recently, up there with Shapiro's 'Contested Will'. Like Shapiro, he is at ease ranging over a huge range of stuff and bringing it to light. Sets the issues of data-handling, prediction and uncertainty in historical and scientific contexts.
The core is Bayes' theory which is fairly mathematical for me to grasp fully but the surprise key seems to be: subjective sense of what is probable must be built into the overall projection; total objectivity is an illusion. RA Fisher comes in for a basting for advocating the elimination of all subjectivity; the fact that he was a smoking/cancer denier in the pay of tobacco companies while puffing away provides an extra coffin-nail! The fun part of the book is how Silver explores implications in many fields: - politics, weather and climate change, epidemiology, earthquakes, terrorism, flight safety and more - throwing anecdotal and analytical light as he goes. Weather forecasters do better when they look out of the window, not just at their charts, just as generals do better if they visit the front-line. Earthquakes remain highly impervious to prediction largely because the essential data is hidden below ground. "Big data", is nothing new;it's been expanding ever since the invention of writing. But now as it grows exponentially, there is a danger in expecting more data (noise) to provide better understanding. What we need are better tools for analysis and pattern discernment, that is, for detecting signal. And, Silver tells us, Bayes theorem is one of the most important.
I was apprehensive of his background in baseball and poker (two fields that I abhor) and confess to skimming those chapters. ( )
  vguy | Feb 1, 2014 |
Nate Silver has become famous for his highly accurate predictions in the 2008 and 2012 US presidential elections. In this excellent book he talks more about the limitations of predictions than about his successes - pleasingly self effacing (particularly after recently reading Taleb's Black Swan). After skewering the ratings agencies for their fundamental role in the global financial crisis of 2008, he polishes off the fatuous talking heads and pundits of TV and other media before moving to a success story - weather forecasting. Through it all he makes clear where forecasting can help, and where its potential is limited. A balanced, nuanced and carefully written book which, unfortunately, won't change the world as much as it deserves.
Read January 2014. ( )
  mbmackay | Jan 30, 2014 |
It's a bit late to be writing this review, but at least we are still in the same calendar year!

This was an extremely enjoyable book to read, especially for someone who has worked in an environment where forecasts, both quantitative and qualitative, have been important. One of the key lessons for me was how to adopt the application of Bayesian forecasting in everyday life and also how to communicate it to others. Incorporating it in to one of my favourite quotes, Bayesian forecasting can be summarised in the words of Keynes:

"when the facts change, I change my opinion, but only to a degree weighted by the quantity and quality of the new facts".

The only instances when it consistently fell over were ironically when Silver is writing about the things he knows most about: sports and politics. An inordinate amount of time is spent describing the world baseball statistics and performance prediction. While the inclusion of this much detail is partly to exhibit Silver's extensive knowledge of the area, it bulks out what is already a rather dense paperback. The sections on politics are similar. ( )
  cyclismotron | Dec 30, 2013 |
In which Nate Silver argues for better forecasting and lionises Baynesian method. Its all neatly set out and impossible to argue with - or rather to do so would be like arguing against the law of gravity.

But I would have liked a broader range of examples; for example is dissection of the poor predictions and forecasting of the financial markets is will known by now, true though it is. His successes in the field of political prediction are also well known - and as he admits himself, competing methods had set a pretty low bar for him to beat. And as he admitted in a trip to Australia, he wouldn't be able to replicate his success there (at least not on a state by state basis) due to lack of data at the state level

He spends some time discussing baseball - a field which is, as he accepts, unusually rich in historical data. This is interesting, and whilst not a baseball fan myself, I could see how baseball is unique. A team game yes, but one where individual clashes predominate. Its unlikely the same approach could be taken to cricket. He also spends time on poker, a topic that personally interests me not at all

The best chapters are those on weather forecasting - where forecasting and predictions are getting better and better , and climate science specifically global warming. And here he nails his argument. Noone disputes the greenhouse effect, few serious people dispute the heating effects of increased greenhouse gases. The problem of course is predicting what will happen; noisy data, patchy historical data, complicating factors galore (sunspots, the cooling effects of the Mt Pinatubo erruption, the cooling effects of sulpher, ENSO etc etc) make predictions difficult. And, as Mr Silver points out, what so called "sceptical" climate scientists disagree about are the predictive models - not the core science

But as Mr Silver points out throughout the book, the goal is not a perfect forecast, but better forecasting. As we get new data we can improve our forecasts. After all, better forecasting is at least an improvement (although in my view, when he tries to use Bayes method to predict terrorist activity, a forecast of the likelihood of an event taking place is not of a great deal of use without knowing in what direction to look for it)

Still - its an excellent book. Should be read in schools. And in government ( )
  Opinionated | Dec 21, 2013 |
Excellent work on predictions, and forecasting. I'd have liked the author to spend a lot less time on the intricacies of sports, but otherwise it's well done. ( )
  Lyndatrue | Nov 27, 2013 |
Showing 1-5 of 35 (next | show all)
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.
added by eereed | editGuardian, Ruth Scurr (Nov 9, 2012)
 
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.
added by eereed | editNew York Times, Noam Scheiber (Nov 2, 2012)
 
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.......
added by marq | editNew York Times, LEONARD MLODINOW (Oct 23, 2012)
 
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.
added by eereed | editSlate, Matthew Yglesias (Oct 5, 2012)
 
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."
 

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Introduction

This is a book about information, technology, and scientific progress.
1
A CATASTROPHIC FAILURE
OF PREDICTION


It was October 23, 2008.
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Amazon.com Amazon.com Review (ISBN 159420411X, Hardcover)

Amazon Best Books of the Month, September 2012: People love statistics. Statistics, however, do not always love them back. The Signal and the Noise, Nate Silver's brilliant and elegant tour of the modern science-slash-art of forecasting, shows what happens when Big Data meets human nature. Baseball, weather forecasting, earthquake prediction, economics, and polling: In all of these areas, Silver finds predictions gone bad thanks to biases, vested interests, and overconfidence. But he also shows where sophisticated forecasters have gotten it right (and occasionally been ignored to boot). In today's metrics-saturated world, Silver's book is a timely and readable reminder that statistics are only as good as the people who wield them. --Darryl Campbell

(retrieved from Amazon Mon, 30 Sep 2013 13:38:29 -0400)

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.

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Penguin Australia

Two editions of this book were published by Penguin Australia.

Editions: 0141975652, 1846147735

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