Test of two distributions/functions

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SUMMARY

The discussion centers on testing the statistical significance between two functions, f1(x,y) and f2(x,y), defined on a table with constraints 1 ≤ f1(x,y) ≤ 1 and 1 ≤ f2(x,y) ≤ 1. The initial suggestion was to use a chi-square test after adding a constant n > 1 to interpret the functions as frequencies. However, it was clarified that statistical significance requires a defined probabilistic process for the functions, and without this, the appropriateness of the chi-square test is questionable.

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phonic
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Dear All,

I have two functions that are defined on a table, i.e. f1(x,y), f2(x,y), where x and y are bin indices, and 1\leq f1(x,y) \leq 1, 1\leq f2(x,y) \leq 1.

I would like to perform some test to show whether f1(x,y) and f2(x,y) are significantly different. Is there some way to do this? I thought of using chi square test for f1(x,y)+n and f2(x,y)+n, where n>1 is a constant added to make f1(x,y) and f2(x,y) interpretable as frequencies.

Thanks a lot!
 
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phonic said:
I thought of using chi square test for f1(x,y)+n and f2(x,y)+n, where n>1 is a constant added to make f1(x,y) and f2(x,y) interpretable as frequencies.

Statistical signficance is not a meaningful concept unless you are dealing with a phenomena that involves probability. To do the usual type of "hypothesis testing" , you must assume the two functions are generated by the same probabalistic process. Until you state exactly what that process is, it isn't possible to say what sort of statistical test is appropriate.

For example if we assume each table is generated by one realization of the uniform [0,1] random variable u according to the formula f(i,j) = (-0.5)(i) - (0.5)(j) + u then it wouldn't make sense to do a chi square test.
 

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