Blogging the Bookshelf

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Entries Tagged as 'Statistical Inference'

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

November 19th, 2012 · Comments Off on Overfit Models – “The Signal and the Noise: The Art and Science of Prediction”, Nate Silver · Modelling, Quotes, Statistics

But the overfit model scores those extra points in essence by cheating—by fitting noise rather than signal. It actually does a much worse job of explaining the real world. As obvious as this might seem when explained in this way, many forecasters completely ignore this problem. The wide array of statistical methods available to researchers […]

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