It looks like all the X's are worthless in estimating Y.
Residuals:
Min 1Q Median 3Q Max
-1.9848 -0.7523 -0.2647 0.5996 2.7807
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -5.067694 6.710096 -0.755 0.479
x1 0.483138 0.384743 1.256 0.256
x2 0.015507 0.009309 1.666 0.147
x3 -0.133613 0.275758 -0.485 0.645
Residual standard error: 1.661 on 6 degrees of freedom
Multiple R-squared: 0.3941, Adjusted R-squared: 0.09113
F-statistic: 1.301 on 3 and 6 DF, p-value: 0.3575
Therefore: the residual standard error is too low (at 1.661) for B1 to be anything other than zero.
If you were going to use the model above to estimate a GPA given that x1 = 6, x2 = 600, and x3 = 2, what would your point estimate be?