I have a multiple regression with 4 independent variables.It has a high
predictive value (R2 = 0.82 and the P-value for F = 0.0004). However, two of
the variables (X1 and X2) hav high P-values for t (0.86 and 0.3,
respectively).

I suspect multicollinearity. However, individual correlation analysis
between each of the X variables is inconclusive. The highest correlation is r
= 0.64. Is that high enough to prove multicollinearity?

Regardless, I was wondering if it is OK to do a multiple correlation
analysis of X1 on the other X variables to prove intercorrelation and
multicollinearity? When regressing X1 on the other variables, r = 0.86; R2 =
0.74. Does that prove multicollinearity?