Fitting Experimental Data to Linear Equations by Regression

Appendix 2B Fitting Experimental Data to Linear Equations by Regression 

Assume that a data set of N experimental readings (shown in Table B.l) has to be fitted to a linear equation of the type y = UiX + Aq- 

Finding the best fit involves calculation of appropriate values for the coefficients Aq and Aj in such a way that the net error between observed values of y and value of y predicted by straight line equation is the least. The least square parameter estimation method estimates 

Equations B.2 and B.3 are linear simultaneous equations written in the matrix form as 

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