ok so i have some data (d) of star counts (N=181), and a model (m = b-Fo where b=5 and Fo-constant flux)(adsbygoogle = window.adsbygoogle || []).push({});

I have found the chi squared value = 216

I know that the number of degrees of freedom here is N-parameters = 181-1 = 180

my question is:

"show that the model is not a good fit to the data, and use an appropriate statistical table to estimate the confidence at which you can reject the hypothesis of a constant source flux"

All i can come up with so far is that if we have a good model we usually expect the chi squared to be approx the number of degrees of freedom which is not the case here. As such one could imply that the data is not a good fit from that.

Also I know that as the degree of freedom is so large the probability function for this will approach gaussian so we would use the gaussian one tailed table.

However, notes i have read talk about comparing the chi squared to some significance level, but i do not know how to calculate this.

any help one getting started and for understanding please?

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# Showing that a model is not a good fit

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