How good is the sinusoidal fit?

[astropi]

First off, this is NOT a homework question! That is, I'm not doing this for any course. So then, here's the question:

I have some data points to which I fit a sinusoidal curve. I get the best (min) chi-square. Now, the question becomes how good a fit is my sinusoid? I was thinking that I could compare my sinusoid with a flat line and see which is a better fit to the data points. How would people suggest I go about doing this? One person suggested a sum of squares, but could not provide me with more than that (he does not remember much except that it "generally works"). I was hoping someone could provide me with much more details (a reference to look up, some examples perhaps?) I know Wikipedia has tons of pages on sum of squares, but I'm not sure which page to go to. Also, if people have other ideas other than sum of squares I am certainly open to it. I know there is something called an F-test, but I don't know how appropriate that would be here? Anyway, I'm hoping for help! Thanks, and yes my statistics is extremely rusty...

 

[Simon Bridge]

The chi-squared statistic is actually the measure of how good the curve fits the data.
http://en.wikipedia.org/wiki/Goodness_of_fit

 

[astropi]

The chi-squared statistic is actually the measure of how good the curve fits the data.
http://en.wikipedia.org/wiki/Goodness_of_fit

Thanks for the response, but that's not what I'm looking for here. I have a few options I'm playing with, but I would still be interested in understanding the F-test if someone can explain how it can be applied to what I described above.