Re: [Phys-L] Model Selection Statistics

[brian whatcott <betwys1@sbcglobal.net>]

Starting with the "Math Is Fun" level:
https://www.mathsisfun.com/data/chi-square-test.html

Continuing with the choices offered in the Indian journal of Ophthalmology:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3116565/

Another Indian source for considering suitable tests:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996580/

Finally an Italian examination of how to validate competing models
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996580/

They all seem to derogate categorical tests like Chi squared for 
graph-like data sources of 80 points.

Brian W
(not sure why American sources do not make a better
showing in my search?)

On 4/12/2019 10:58 AM, Paul Nord wrote:
> "Ask n statisticians, get C(n,k) opinions."
>     - me, just now
>
> Suppose I have some physics data binned into 80 bins.  And I have two
> models which propose to fit some characteristic of interest and a
> non-linear background.  One is a simple polynomial.  The other is a more
> complicated.  I can calculate a reduced chi square for each data fit.
>
> What's the best way to compare the two models?
> I have a dim memory of this lecture.  Does someone have a good translation
> of said lecture into terms a physicist can understand?
>
> Paul
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