Our “anecdotal” brain sucks up all the sensational news a media (vying for higher ad revenues) can muster. This results in some skewed gut feelings of what we should be afraid of.
Wired’s book review of Dan Gardner’s The Science of Fear includes a quiz that is worth taking.
August 7, 2008
Posted by
pragmasynesi |
behaviour, brain, decision making, statistics |
fear, media, probabilities |
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“All models are wrong, but some are useful” — I love that quote. For me it highlights the raison d’etre of science: to predict and therefore to increase control. I don’t agree with the article that theories and models will become obsolete, but it is time to add some new tools to the set of predicting tools we already have. And use the most useful ones.
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August 7, 2008
Posted by
pragmasynesi |
statistics |
science, model, theory, hypothesis, Google |
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http://www.economist.com/science/displaystory.cfm?story_id=9645336
The article highlights a typical problem with statistical models that use many “runs” to come up with most likely results — that is, how to vary the parameters for each “run”. These kind of models are used in many places, for example in determining whether someone’s retirement fund invested in the stock markets will be sufficient given the market volatilities.
In the example cited in the article, the parameters were varied on a linear basis. From my perspective, that’s just sloppy: each parameter should have its own statistical distribution (what is its most common value? how far up/down the scale does it vary? etc.) and the values that go into each “run” should be determined based on that distribution. So for parameters that are the same except in the way that they are expressed, the distribution curve would look the same and there would be no problem.
The problem, which the article does not sufficiently stress, is that a lot of the parameters may be related in a way that is much more complex, and what’s even more important, in a way we may not know. In the first instance, making the model more complex (e.g. using a small model to determine the parameters that go into the main model) would lessen the problem. But what we do not know can severely affect the outcome.
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August 16, 2007
Posted by
pragmasynesi |
statistics |
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