Fcalc – the Global Test for Regression Significance

A statistically significant Fcalc (i.e. one that passes the Fcritical threshold, based on your degrees of freedom) can indicate that your model as a whole is meaningful.
This test is really applicable for multiple regressions, where there is more than one slope coefficient (b1, b2, b3 … bi), as a t-test will not work for multiple regression models.
The F-test is a one tailed test.
The null hypothesis will be that the Fcalc is less than or equal to the Fcritical and you will be looking to reject the null with an Fcalc > Fcritical.
A rejection of the null indicates that at least one of the slope coefficients is significant and there is some validity to the model.
Fcalc has a math relationship with RSS (and MSSR), SSE (and MSSE), and TSS.

A statistically significant Fcalc (i.e. one that passes the Fcritical threshold, based on your degrees of freedom) can indicate that your model as a whole is meaningful.
This test is really applicable for multiple regressions, where there is more than one slope coefficient (b1, b2, b3 … bi), as a t-test will not work for multiple regression models.
The F-test is a one tailed test.
The null hypothesis will be that the Fcalc is less than or equal to the Fcritical and you will be looking to reject the null with an Fcalc > Fcritical.
A rejection of the null indicates that at least one of the slope coefficients is significant and there is some validity to the model.
Fcalc has a math relationship with RSS (and MSSR), SSE (and MSSE), and TSS.