Pragma Synesi – interesting bits

Compendium of interesting bits I come across, with an occasional IMHO

What You Don’t Know Can Kill You

Our innate instincts to recognize the probabilities of dangers are not always accurate (or useful) in our modern world.  But if you understand this, you can use your rational mind to try to alter your behaviour accordingly.  From Discover magazine, July-August 2011 edition:

What You Don’t Know Can Kill You

Humans have a perplexing 
tendency to fear rare threats such as shark attacks while blithely 
ignoring far greater risks like 
unsafe sex and an unhealthy diet. Those illusions are not just 
silly—they make the world a more dangerous place.

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September 12, 2011 Posted by | behaviour, brain, decision making, emotions, statistics | , , | 1 Comment

What Health Stats Really Mean

Statistical illiteracy becomes a big problem when people make health decisions.  So why isn’t statistics taught to everyone early in school?  And more importantly, why isn’t it a requirement for doctors?

From Scientific American Mind,  April 8, 2009:

Knowing Your Chances: What Health Stats Really Mean

Learn how to put aside unjustified fears and hopes and how to weigh your real risk of illness–or likelihood of recovery

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October 6, 2009 Posted by | decision making, health, statistics | , , , , , , , , | 1 Comment

What should you really fear?

Our “anecdotal” brain sucks up all the sensational news the 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. For example,

What was the total death toll of the 9/11 terrorist attacks?

  1. 3,000
  2. 4,595
  3. 20,000

August 7, 2008 Posted by | behaviour, brain, decision making, statistics | , , | Leave a comment

The End of Theory?

“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.



The End of Theory: The Data Deluge Makes the Scientific Method Obsolete

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August 7, 2008 Posted by | statistics | , , , , | 4 Comments

One problem with models

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 | statistics | Leave a comment