Team:KULeuven/Data/Overview

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Introduction

When we developped the theoretical model of our system (see Modeling-section), the value of the different parameters (kinetic constants) were taken from different sources and will not fully represent our scheme. This was performed to see if some unexpected behaviour was expected from that. Unfortunately, this kind of approximation do not have a predictable value if we do not know exactly the value of the model parameters.

Data analysis involves manipulating experimental data with the objective of extracting useful information. This then allows us to test our original hypotheses surrounding the problem, and in doing so, test the stringency/validity of our theoretical model. If the model proves to be valid, data analysis likewise provides a means of parameter extraction essential in rendering our theoretical model more realistic (as it gleans parameters from actual expimental data).