Fitting Nonlinear Data to a Linear Equation: Manual Calculation Process

AI Thread Summary
To fit nonlinear data to a linear equation manually, start by recognizing that the equation is linear in the coefficients A, B, and C, despite being nonlinear in terms of x. You can substitute your data pairs (x1, y1), (x2, y2), and (x3, y3) into the equation to create a system of linear equations. Solve this system using methods such as substitution or elimination to find the values of A, B, and C. It is feasible to perform these calculations manually given the limited number of data points. This approach allows for a clear understanding of the relationship between the variables without relying on software.
Doctor_Doom
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Hey guys I'm completing an experiment and I'm required to extrapolate data by performing nonlinear curve fitting.

I have 3 sets of data: (x1, y1); (x2, y2); (x3, y3).

I'm required to fit the above mentioned sets of data to the following equation :

[PLAIN]http://img245.imageshack.us/img245/8121/37594905.png

In order to gain maximum marks manual operations would be required. Thus I would prefer if someone could provide me with an initial hint on how to start a manual calculation process.

I'm assuming that performing the calculations manually for the curve fitting would not be a huge task due to the fact that there are only 3 sets of data points.

So I'm hoping someone could provide me with the starting hint on how to perform the manual (NO SOFTWARE USED) calculations for the curve fitting of the above equation.
 
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Just plug in your data pairs for x and y, and solve the linear system of this three equations for A, B, C.

ehild
 
Additionally, the problem isn't nonlinear. The equation is linear in the unknowns A, B, C as implied in ehild's reply. It is nonlinear in x, but the x's are known.
 
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