What is the correct formula for the reduced Chi square?

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SUMMARY

The correct formula for the reduced Chi square (χ²) and root mean square deviation (RMSD) is a point of confusion among users. The formula for RMSD is given as χ = √(1/N ∑((yᵢ - ŷᵢ) / δyᵢ)²), while the reduced Chi square is expressed as χ = √(1/(N-m) ∑((yᵢ - ŷᵢ) / δyᵢ)²), where N is the number of data points, m is the number of model parameters, y is the measured data, ŷ is the calculated data, and δyᵢ is the measurement error. The optimal value for reduced χ² is indeed 1, indicating a good fit, and minimizing the reduced χ² leads to the best model fit.

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patric44
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Homework Statement
what is the correct formula of reduced Chi square
Relevant Equations
\Chi^2
Hi all
I want to calculate the reduced Chi square and root mean square deviation RMSD of some data points that i have, but I am confused about the correct formula for each of them, which one is the correct one. I found this formula in a paper where they referred to it as the RMSD :
$$
\chi=\sqrt{\frac{1}{N}\sum_{i}^{N}\left(\frac{(y_{i}-\tilde{y}_{i})}{\delta y_{i}}\right)^{2}}
$$
and in some books the same formula with little modification (instead of ##N## they put the degrees of freedom) as :
$$
\chi=\sqrt{\frac{1}{N-m}\sum_{i}^{N}\left(\frac{(y_{i}-\tilde{y}_{i})}{\delta y_{i}}\right)^{2}}
$$
which one is reduced ##\chi^{2}## and which is RMSD if any of them?!
another question why i read that we need to minimize the value of reduced ##\chi^{2}## to get the best fit, isn't the optimum value is 1 ?! , shouldn't we minimize 1-##\chi^{2}## or what?
I will appreciate any help, thanks in advance
 
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Please carefully define the elements in these formulae, particularly ##\tilde{y}_{i}## and
##\delta y_i ## and what is m?)
 
hutchphd said:
Please carefully define the elements in these formulae, particularly ##\tilde{y}_{i}## and
##\delta y_i ## and what is m?)
##y## is the measured data
##\tilde{y}## is the calculated data from a specific model
##\delta y_i ## is the error in measuring ##y##
##m## the number of parameters of the model
I am not talking about the so called category chi2. I mean the other one
 
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I think the formula with the m is appropriate. Very often m=1 when the the mean value is taken as a "fitted" parameter from the data. I have no idea about the names and categories of these things sorry.
 
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