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It depends on the degrees of freedom for the f-test.
A T test is used to find the probability of a scenario given a specific average and the number of degrees of freedom. You are free to use as few degrees of freedom as you wish, but you must have at least 1 degree of freedom. The formula to find the degrees of freedom is "n-1" or the population sample size minus 1. The minus 1 is because of the fact that the first n is not a degree of freedom because it is not an independent data source from the original, as it is the original. Degrees of freedom are another way of saying, "Additional data sources after the first". A T test requires there be at least 1 degree of freedom, so there is no variability to test for.
(r-1)x(c-1)
Mass and damping are associated with the motion of a dynamic system. Degrees-of-freedom with mass or damping are often called dynamic degrees-of-freedom; degrees-of-freedom with stiffness are called static degrees-of-freedom. It is possible (and often desirable) in models of complex systems to have fewer dynamic degrees-of-freedom than static degrees-of-freedom.
The data sets determine the degrees of freedom for the F-test, nit the other way around!