[SciPy-User] [OT] Bayesian vs. frequentist

Travis Oliphant travis@continuum...
Tue Feb 14 15:56:22 CST 2012


can I frame this :-)

+10


On Feb 14, 2012, at 1:40 PM, Sturla Molden wrote:

> 
> After having worked with applied statistics for ~15 years, I have 
> reached this conclusion... ;-)
> 
> 
> Sturla's 20 propositions on Bayesian vs. classical statistics:
> ==============================================================
> 
> 1. For simple data, a figure is sufficient, nobody really cares.
> 
> 2. For dummy problems with known facit, Bayesian methods tend to be the 
> more accurate.
> 
> 3. Bayesian methods include prior knowlege. A horse of 400 g is a priori 
> less likely than a horse of 400 kg. Frequentists say this is too subjective.
> 
> 4. Bayesian methods are easier to interpret. Few understand a 
> frequenctist confidence interval, albeit everybody they think they do.
> 
> 5. Hypothesis testing: Bayesians answer the question we ask. Freuentists 
> don't.
> 
> 6. Economists investing their own money are bayesians.
> 
> 7. Economists investing your money are frequentists.
> 
> 8. For basic medical research, nobody cares.
> 
> 9. Drug trials: For getting an FDA application approved, frequentists 
> often yield a more 'significant result'.
> 
> 10. Drug trials: For in-hose liability estimates, Bayesian methods are 
> the safer.
> 
> 11. Frequentists can always get more significant results by "sampling 
> more data".
> 
> 12. Frequentists don't care about stopping rules, even though they should.
> 
> 13. Bayesians don't care about stopping rules bacause they don't have to.
> 
> 14. "Significant" does not mean "important". Any tiny difference can be 
> made statistically significant.
> 
> 15. For interpreting clinical lab tests, Bayesian methods prevail, e.g. 
> predictive values.
> 
> 16. Engineers who know their mathematics use Bayesian methods.
> 
> 17. Social scientists who don't know their mathematics are frequentists.
> 
> 18. SPSS, Excel, Minitab, and SAS make it easy to be an ignorant 
> frequentist.
> 
> 19. No tool make it easy to be an ignorant bayesian.
> 
> 20. Competent analysts use R, Fortran, Matlab or Python.
> 
> 
> 
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