Blogging the Bookshelf

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Entries Tagged as 'Data'

Political Advice and Story Telling – “The Victory Lab: The Secret Science of Winning Campaigns”, Sasha Issenberg

December 5th, 2012 · Comments Off on Political Advice and Story Telling – “The Victory Lab: The Secret Science of Winning Campaigns”, Sasha Issenberg · Campaigning, Data, Narrative, Politics

“A lot of what gets done on campaigns gets done on the basis of anecdotal evidence, which often comes down to who is a better storyteller. Who tells a better story about what works and what doesn’t work?” says Christopher Mann, a former executive director of the New Mexico Democratic Party. .. The people who […]

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The Origins of Statistical Inference – “The Victory Lab: The Secret Science of Winning Campaigns”, Sasha Issenberg

December 4th, 2012 · Comments Off on The Origins of Statistical Inference – “The Victory Lab: The Secret Science of Winning Campaigns”, Sasha Issenberg · Data, Policy, Statistical Inference, Statistics

Not far from Fisher, a young economist named Austin Bradford Hill was growing similarly impatient with the limits of statistics to account for cause and effect in health care. In 1923, for example, Hill received a grant from Britain’s Medical Research Council that sent him to the rural parts of Essex, east of London, to […]

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Shallow Betting Markets – “The Signal and the Noise: The Art and Science of Prediction” – Nate Silver

November 23rd, 2012 · Comments Off on Shallow Betting Markets – “The Signal and the Noise: The Art and Science of Prediction” – Nate Silver · Data, Prediction

I don’t know that political betting markets like Intrade are all that good right now—the standard of competition is fairly low. Intrade is becoming more popular, but it is still small potatoes compared with the stock market or Las Vegas. In the weeks leading up to the Super Tuesday primaries in March 2012, for instance, […]

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The Limitations of Statistical Significance – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver

November 22nd, 2012 · Comments Off on The Limitations of Statistical Significance – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver · Data, Statistical Inference, Statistics

The bigger problem, however, is that the frequentist methods—in striving for immaculate statistical procedures that can’t be contaminated by the researcher’s bias—keep him hermetically sealed off from the real world. These methods discourage the researcher from considering the underlying context or plausibility of his hypothesis, something that the Bayesian method demands in the form of […]

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More Data Means More Noise – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver

November 21st, 2012 · Comments Off on More Data Means More Noise – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver · Data, Prediction, Statistical Inference, Statistics

As there is an exponential increase in the amount of available information, there is likewise an exponential increase in the number of hypotheses to investigate. For instance, the U.S. government now publishes data on about 45,000 economic statistics. If you want to test for relationships between all combinations of two pairs of these statistics—is there […]

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In Medicine, Stupid Models Kill People – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver

November 20th, 2012 · Comments Off on In Medicine, Stupid Models Kill People – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver · Data, Prediction, Statistical Inference, Statistics

Much of the most thoughtful work on the use and abuse of statistical models and the proper role of prediction comes from people in the medical profession. That is not to say there is nothing on the line when an economist makes a prediction, or a seismologist does. But because of medicine’s intimate connection with […]

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Out of Sample Problems – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver

November 16th, 2012 · Comments Off on Out of Sample Problems – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver · Causation and Correlation, Data, Prediction, Statistics

But forecasters often resist considering these out-of-sample problems. When we expand our sample to include events further apart from us in time and space, it often means that we will encounter cases in which the relationships we are studying did not hold up as well as we are accustomed to. The model will seem to […]

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Risk and Uncertainty – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver

November 16th, 2012 · Comments Off on Risk and Uncertainty – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver · Data, Prediction

Risk, as first articulated by the economist Frank H. Knight in 1921, is something that you can put a price on. Say that you’ll win a poker hand unless your opponent draws to an inside straight: the chances of that happening are exactly 1 chance in 11. This is risk. It is not pleasant when […]

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The Predictable Housing Bubble – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver

November 15th, 2012 · Comments Off on The Predictable Housing Bubble – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver · Data, Economics, ICT, Policy

Paul Krugman, the Nobel Prize–winning economist, wrote of the bubble and its inevitable end in August 2005. “This was baked into the system,” Krugman later told me. “The housing crash was not a black swan. The housing crash was the elephant in the room.” Ordinary Americans were also concerned. Google searches on the term “housing […]

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What You Can’t State Your Innocence, Proclaim Ignorance – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver

November 14th, 2012 · Comments Off on What You Can’t State Your Innocence, Proclaim Ignorance – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver · Data, Prediction, Quotes

Nobody saw it coming. When you can’t state your innocence, proclaim your ignorance: this is often the first line of defense when there is a failed forecast.

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