When forcing intercept to zero, why JMP does not provide R-squared?

[#1]

Hello, I have some questions. 

When I have a linear model in JMP, I want to force intercept to zero.

So, In Fit Special,  I chose "Constrain Intercept to 0" then I got the new output from JMP.

My questions are

1) why JMP does not provide R-squared when intercept becomes zero? 

2) R-squared is calculated by SSR/SST, can I calculate R-squared by myself using the data JMP provides? If I calculated by myself, it's higher than before. Is this possible? In this case, it says R-squared is 99%. Can I say this R-squared is correct?

Thanks, 

[#2 · Accepted solution]

This case is one of "just because you can doesn't mean you should."

Yes, the sum of squares that are normally used to compute R square are provided. But the resulting ratio has no meaning. R square is called the "coefficient of determination" in linear regression. When R square equals 1, then all the variation in Y is explained or determined by variation in X. (That is not a statement about causation.) When R square equals 0, then Y is independent of X. It is, therefore, the mean of Y for all X. But your null hypothesis is that Y = 0. So the ANOVA might be statistically significant, but the R square is undefined.

See this article for more information.