Imperial/Dry Lab/Data Analysis

From 2007.igem.org

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(Representative example)
(Principle of non-linear regression/curve fitting by least-squares)
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Our approach to data analysis utilizes curve/shape-fitting by non-linear regression (employing the least-squares method).
Our approach to data analysis utilizes curve/shape-fitting by non-linear regression (employing the least-squares method).
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==Principle of non-linear regression/curve fitting by least-squares==
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==Principle of method of parameter extraction==
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The method of non-linear least squares is employed.
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Theory<br>
Theory<br>
Theory<br>
Theory<br>

Revision as of 14:45, 22 October 2007

Contents

Data Analysis

Introduction

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 representative 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).

Our approach to data analysis utilizes curve/shape-fitting by non-linear regression (employing the least-squares method).

Principle of method of parameter extraction

The method of non-linear least squares is employed.

Theory
Theory
Theory
Theory

Representative example

Consider the following model