Posts Tagged ‘prediction’

Seemingly random attacks and a shadowy, mysterious enemy are the hallmarks of insurgent wars, such as those being fought in Afghanistan and Iraq. Many social scientists, as well as the military, hold that, like conventional civil wars, these conflicts can’t be understood without considering local factors such as geography and politics. But a mathematical model published today in Nature (see Nature 462, 911–914; 2009) suggests that insurgencies have a common underlying pattern that may allow the timing of attacks and the number of casualties to be predicted.

A couple of issues to consider:

Say these researchers are “right”, what would we do then with a prediction of insurgency?  How would we prevent attacks and under what justification?

Does the data consider all failed or near insurgencies?

Are Nature and the authors beyond the scope of scientific research make an assertion that a model for human insurgency has been found before any real verification?

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The news is a maniacal scramble to make sense of the current financial situation around the world.

Predictions, ____ expert from _____ investment research firm, advice, soothsaying, modeling, bear vs. bull, Fed should do this, Fed shouldn’t do this…. and so on.

A truth I got comfortable with a long time ago but had reinforced over the last three weeks in my life.

Your model can only be as predictive as the thing you are modeling.

– Jason Cawley, Wolfram Research (and probably others…)

That’s a stupid statement, right? Duh.  I know that.

Really think about it though.  and then consider these things and your interpretation of them

  • weather forecasts
  • endless dow jones index reports
  • Political polls
  • compatibility tests in online dating
  • SAT scores
  • TSA profiling at airports
  • Annual budgeting for businesses
  • Or go through the latest in the news

All of these “indicators” attempt to predict complex systems/situations.  Those systems have to show some stability, some simplicity to ever give way to useful prediction (useful = do you get info you can use elsewhere and with enough time/energy to use it).

There is potential to get some local or short term prediction due to local or short term stability.  However, to effectively use that over time you need to be able to predict when that stability yields to a new pattern. That is where it gets difficult.

Yes, you can aggregate a lot of these indicators to produce some sort of statistical sample.  Usually though, you’re simply hiding the intesting stuff in the errors in your statistical model.  Washing out the outliers as “noise”.  The problem is, especially in the indicators above, it’s the outliers that matter! But I digress…

Point for financial pundits: national and global economics itself is complex. no simple model, simple statement, simple index can accurately model it. not even poorly.

Agree or Disagree?  Let’s have a discussion.

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