Granger causality uses the notion of VAR models where we can create two models one using the prediction of X alone and another using X and Y. If X,Y model performs better we can say that X causes Y. At many web resources, there is a mention of F-score and p-value to determine Granger causality. Where do they fit in with VAR models for determining Granger causality
I am not sure if I understand your question... Consider a VAR model for ($x,y$). You test joint zero restrictions on all lags of $x$ in the equation of $y$ to find whether $x$ Granger-causes $y$. The test is an $F$-test, and the test statistic has an associated $p$-value. If the $p$-value is low enough, you reject the null hypothesis of noncausality in favour of causality. Is anything missing here?