©2014. Published in Landslide, Vol. 6, No. 5, May/June 2014, by the American Bar Association. Reproduced with permission. All rights reserved. This information or any portion thereof may not be copied or disseminated in any form or by any means or stored in an electronic database or retrieval system without the express written consent of the American Bar Association or the copyright holder.
The survival of homo sapiens has depended upon our ability to analyze quickly and then act upon the plethora of data that continuously assaults our senses. Just as our ability to notice a crouching tiger in the bamboo thicket can lead to a life or death situation so too in our modern world, we try to make sense of a barrage of information and sensory stimulation by envisioning patterns that enable us to make predictions. Whether we infer by interpolation between data sets or extrapolate to predict a future event such as an earthquake, we need to see relevant data—the signal—and discard the rest—the noise. The field of statistics provides many tools that help us make useful and likely predictions for modern day problems and discard fallacious inferences that we may construct from intuition and apparent obviousness. Nate Silver’s book, The Signal and the Noise: Why So Many Predictions Fail but Some Don’t applies one of these statistical tools, the Bayesian Method1 to look at phenomena from gambling to sports events, to earth quakes and weather predictions. He succeeds in bringing statistical analysis alive—and front and center to our thinking.
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