Calculating p value for non-linear fit

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Tom
Tom on 10 Jul 2012
Matlab documentation has the following on the calculation of the p statistics, implemented in the corrcoef function:
"The p-value is computed by transforming the correlation to create a t statistic having n-2 degrees of freedom, where n is the number of rows of X. The confidence bounds are based on an asymptotic normal distribution of 0.5*log((1+R)/(1-R)), with an approximate variance equal to 1/(n-3)."
I'm sorry, but the above text is Chinese for me. If I fit a set of data points [x y] to an arbitrary function, calculating the R squared is very easy. But how do I go about adapting the ttest so that I find the probability that the fit equation actually accounts (R squared), say, 0.9 (90%) of the variance in the data?
Thanks in advance!

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