Lecture 31. 


Least squares curve fitting. 

I started with a geometric approach to derive the system of equations used to obtain the "best" line in the least squares sense that fits a set of data points.

I then used the normal equations approach to derive the same equations. The derivation expresses everything in terms of vectors and matrices and generalized very easily to the more general case where we are fitting a linear combination of functions to a set of data points.
 

Posted: Tue - November 22, 2005 at 11:48 AM          


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