First, experimental data is produced in the form of a progress curve for either s or p (we have used lower case letters to denote the concentrations of S and P respectively). Second, the experimental data is then used to estimate both K M and V by optimally fitting the model ( ) through the utilization of either a deterministic (i.e., such as Levenburg-Marquardt) or a stochastic (Markov Chain Monte Carlo) algorithm. In general, one seeks to estimate kinetic constants with an expression that contains the fewest number of parameters: this is why the MM equation is more attractive than the complete set of mass action equations.