[Ifeffit] uncertainties in "relative" values

Scott Calvin SCalvin at slc.edu
Sat Feb 26 23:24:04 CST 2005


Hi Matt,

I tried that, before realizing it didn't really do anything. 
Performing a multi-dataset fit with two guessed variables, say size_A 
and sizeA_v_sizeB, is of course completely equivalent to just having 
the two sizes as guessed variables.  And if size_A is set to some 
arbitrary (but reasonable) value, sizeA_v_sizeB is equivalent to just 
fitting size_B, and produces the "absolute" uncertainty again. This 
would be different if the fit were truly multi-dataset in the sense 
that we had parameters in common between samples, so that 
constraining the size of A had some effect on the fit for B. But the 
parameters that are in common, like S02, we constrained to a standard 
rather than refining through a multi-dataset fit.

I like your analogy to airline tickets...that is something like the 
situation we seem to have.

--Scott Calvin
Sarah Lawrence College

>Hi Scott,
>
>Would it make sense to define a factor between the size of the
>two (or more) particles, say "sizeA_v_sizeB" and vary *that* in
>a fit of the two particles, keeping all the other things
>(k-weight, ranges, etc) the same for the two fits?  That is,
>instead of asking "what is the size of particle A and what is
>the size of particle B?", ask "what is the size of particle A
>and how much bigger is particle B?". If you're observations are
>right, sizeA_v_sizeB should be statistically different from 1.
>
>--Matt
>
>PS:  The price of airline tickets vary widely with many factors,
>but for any given flight, the price (starting "retail" price) of
>a first class ticket is always higher than a coach ticket.  Of
>course, the coach ticket on some flights can easily be twice the
>price of a first class ticket on other flights.  But everyone
>knows first class is always more expensive than coach. ;).



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