Every time we choose a route to work, decide whether to go on a second date, or set aside money for a rainy day, we are making a prediction about the future. Yet from the global financial crisis to 9/11 to the Fukushima disaster, we often fail to foresee hugely significant events. In The Signal and the Noise, the New York Times’ political forecaster and statistics guru Nate Silver explores the art of prediction, revealing how we can all build a better crystal ball.
In his quest to distinguish the true signal from a universe of noisy data, Silver visits hundreds of expert forecasters, in fields ranging from the stock market to the poker table, from earthquakes to terrorism. What lies behind their success? And why do so many predictions still fail? By analysing the rare prescient forecasts, and applying a more quantitative lens to everyday life, Silver distils the essential lessons of prediction.
We live in an increasingly data-driven world, but it is harder than ever to detect the true patterns amid the noise of information. In this dazzling insider’s tour of the world of forecasting, Silver reveals how we can all develop better foresight in our everyday lives.
Every time we choose a route to work, decide whether to go on a second date, or set aside money for a rainy day, we are making a prediction about the future. Yet from the global financial crisis to 9/11 to the Fukushima disaster, we often fail to foresee hugely significant events. In The Signal and the Noise, the New York Times’ political forecaster and statistics guru Nate Silver explores the art of prediction, revealing how we can all build a better crystal ball.
In his quest to distinguish the true signal from a universe of noisy data, Silver visits hundreds of expert forecasters, in fields ranging from the stock market to the poker table, from earthquakes to terrorism. What lies behind their success? And why do so many predictions still fail? By analysing the rare prescient forecasts, and applying a more quantitative lens to everyday life, Silver distils the essential lessons of prediction.
We live in an increasingly data-driven world, but it is harder than ever to detect the true patterns amid the noise of information. In this dazzling insider’s tour of the world of forecasting, Silver reveals how we can all develop better foresight in our everyday lives.
More noise than signal Mr Silver clearly knows what he is talking about, but I’m less sure he knows how to talk about it. I assume he set out to write a chatty, non-challenging book, but the result is light on substance and structure.The Nobel prize-winning physicist Niels Bohr famously said ‘Prediction is very difficult, especially if it’s about the future’. This pretty much sums up the first half of the book. Yes, the detail about the financial crisis, weather forecasting, earthquakes etc is mildly interesting, but in relation to prediction, you will be wading through a lot of noise to extract the signal (‘human nature makes us over-confident predictors’, ‘without either good theory or good empirical data, you may as well just guess’,’the most confident pundits are usually the worst’ etc).The substance of the book comes in twenty pages in the middle, where Silver introduces Bayesian logic (I learnt in maths classes at school when I was fourteen so it wasn’t new to me, and it doesn’t need 200 pages of build up). The best section is where Silver contrasts Bayesian logic to Fisherian logic. Fisher created the maths that is used almost universally in medical and social science research to prove the efficacy of a treatment or theory. Silver explains how flawed this maths is – which is presumably why two thirds of the positive findings claimed in medical journals cannot be replicated. This is pretty heady stuff.Silver claims that the second half of the book is about how to make predictions better. It is mostly more examples of failure, this time in chess, investment, climate and terrorism, with a few asides that might be considered signals (‘testing is good’, ‘groups/markets tend to make better predictions than individuals’). The exception is the section on poker, which delivers the strongest message in the book: good gamblers think in probabilities (rather than dead certs) – when these probabilities diverge from the odds on offer by a suitable margin, they may place a bet. Bad poker players lose a lot more than good poker players make. The best is the enemy of the good…Of course, the point of the book is that there is no silver bullet – good prediction requires detail, nuance, hard work, honesty and humility. It would be wrong to expect a check list for success at the end, and naturally, there isn’t one. Even so, you are left with a craving for clarity.’The Signal and the Noise’ is a pleasant enough read, but it is mostly anecdote. Rather ironically, you are left to sort out the signal from noise yourself.
Interesting, but a bit shallow Silver has some good ideas, and he is to be commended for scruplously footnoting his references, but there are some mistakes (the “cows would rate this” was from an S&P analyst,not Moody’s) and he utilises heuristics he criticises elsewhere (lazily claiming the industrial revolution happened, just like that, in 1775 with the excuse “it is a nice round number”).My two main criticisms for non Americna readers is that it is quite US centric (I don’t care about baseball, and the general moneyball story is impossible to avoid) and the main philosophical stuff (which was most useful and ineresting to me) makes up a small portion of the book, the majority with various examples where he makes the same arguments with interview of different people that are somewhat non-questioning.He gives some useful examples throughout the book, covering meteorology, earthquakes, transmision of viruses, but it still feels as if it could have been cut. The stuff on Bayes is interetsing but really skates over the issue of how you come up with a Bayesian prior when you can’t iteratively improve them because you do not have many data points. Given the time he spends looking at the financial crisis, this is a flaw as it reduces the “wow, Bayes is really useful” impact when it cannot offer that much resolution to the problem of predicting economic and financial crises, the key predictive failure he cites.Even so, as a way of getting people to think a bit more deeply about what it is to make a prediction and how to know if it was well constructed, and how to integrate concepts of epistemology, it is a useful introductory book.
Good in parts It’s readable in the early stages, and provides an easy introduction to Bayesian probability. The stumbling blocks are the interminable sections on baseball and poker. Unless you understand and are interested in these two diversions, you’ll lose the will to live. That’s a pity, because the man obviously knows what he’s talking about, witness his success in analysing poll data for the US elections.