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i have some data (star counts) and i have a model and i want to perform min chi squared

so if i call my data di, and my model mi with std dev = [itex]\sigma[/itex]i = 1

then [itex]\chi^2 = \sum \frac{(di - mi)^2}{\sigma i^2}[/itex]

no my model is this mi = bi - Fo where bi is the background which has been assumed to be 5, and Fo is some constant flux. from this i am thus assuming that the data is ecpected to be a flat line.

Now i want to determine the min ch squared estimate for Fo, but i am not sure how.

I have gotten this far:

[itex]\frac{d\chi ^2}{dFo} = -2\sum \frac{(di - bi - Fo)}{\sigma i^2}[/itex] = 0

any help is appreciated thanks

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# Minimum chi squared estimation

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