Distinguish noise from signal-the predictions would be more accurate
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Home General

Distinguish noise from signal-the predictions would be more accurate

Archive ManagerArchive Manager
Dec 15, 2012, 12:00 am IST
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The Signal and the Noise: The Art and Science of Prediction, Nate Silver, Allen Lane, Penguin Books, Pp 534 (HB), £25.00

UNCONSCIOUSLY, our mind predicts several things in a day. On some we are right, on some wrong. But when we predict consciously and lose, we feel the disappointment and at times anger. Nate Silver in The Signal and the Noise: The Art and Science of Prediction discusses the concept, significance and ways of predicting, right. He has included all walks of life—economics, science, money management, relationship, tragedies and natural calamities—in this study. “Prediction is important because it connects subjective and objective reality,” he says.

Silver points out how wrong predictions were responsible for the recent and on-going economic depression. “I am convinced that the best way to view the financial crisis is as a failure of judgment—a catastrophic failure of prediction. These predictive failures were widespread, occurring at virtually every stage during, before and after the crisis and involving everyone from the mortgage brokers to the White House.” The credit rating agencies, selling financial propositions had predicted a default rate of 0.12 per cent while granting AAA ratings to several investments. The actual default rates turned out to be 28 per cent. These predictions were not so much ‘bad luck’ or wrong predictions as they were will-full greedy to maximise profits for a few. As someone said, “They are not stupid people. They did not want the music to stop.”

The meteorological science thrives on predictions. Based on their readings of the past, they predict sunlight and rains and clouds and winds. And most of the time people do not take it seriously because of their past experience with weather forecasts. Silver gives two examples of how human lives were lost because people did not believe the predictions or the forecasts. An earthquake in L’Aquila in Italy in 2009: A local technician working in the National Institute of Physics had claimed to have read increased levels of radon in the area. A warning was sounded. But when no tremor came in the next 24 hours, people relaxed. It came a little after 24 hours, killing 300 people. Similar was the case with floods in North Dakota. Most predictions are based on statistics, especially true of the weather. Here he cracks a joke at a statistician who drowned in three feet deep water on average.

Till 9/11 happened no body predicted such an act, despite several intelligence inputs. Most would not have believed such a prediction. But after that day, that hour, people are willing to believe anything, if one were to go by the nature of rumours. We should not miss the signal for noise. “This is why it is so crucial to develop a better understanding of ourselves, and the way we distort and interpret the signals we receive, if we want to make better predictions.”
Silver gives guidance on how to predict rightly. With the internet age, we receive enormous amount of information. “This volume of information is increasing exponentially. But relatively, little is this information is useful—the signal-to-noise ratio may be waning. We need better ways of distinguishing the two. This book is less about what we know than about the difference between what we know and what we think we know…”

In that he recommends the application of Bayes’s theorem. Bayes suggested that a subjective degree of belief should account for evidence. Silver also suggests that “If you cannot make a good prediction, it is very often harmful to pretend that you can. I suspect that epidemiologists, and others in the medical community understand this because of their adherence to the Hippocratic oath Primum non nocere:First, do no harm.”

Till reading Nate Silver one did not realise there was so much to prediction science. Somehow the word was associated with the concept of unfounded. That would indeed be far from truth, because all predictions are subjective and are influenced by our knowledge and information.

Nate Silver is a statistician and political forecaster at the New York Times who earned acclaim when he correctly predicted 49 out of 50 states during the 2008 US presidential elections. In the hands of Silver prediction has become an art and a science. Next time when we wonder what is going to happen next, we must apply the principles of Silver.
(Allen Lane, Penguin Books Ltd80 Strand, London, WC2R, ORI England)

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