A temporal sampling strategy is explored for identifying the parameters for a state model of a dynamic system. This results in the analysis of upper and lower bounds for the sample period of equally spaced discrete-time experimental data required to completely describe the dynamics of a continuous-time system. Through Monte Carlo simulations applied to an example system, a statistical interpretation of the sampling interval bounds is obtained. Application of the results of this analysis is general within the class of compartmental systems.