Biosensor technology can lack methods to iteratively validate system outputs (i.e., signals) concomitantly with the development of mathematical models. We evaluated a nonmodified fiber optic enzymatic biosensor (FOEB-Escherichia coli BL21 (DE3) pGELAF+) sensing dichloroethane with a predictor-response statistical form. The linear regression technique applied with MATLAB functions correlated FOEB parameters to sensing responses that could be used to identify system characteristics and interactions. A FOEB specific metric (i.e. normalized sensitivity) is shown to be significant as a mixed sensing correlation metric suggesting that similar development parameters could be related to engineering design paradigms for biosensor (or whole cell biosensor) systems.