Weighted Linear Regression with Errors in

The following data were recorded during the preparation of a calibration curve, where S eas and s are the mean and standard deviation, respectively, for three replicate measurements of the signal. 

Determine the relationship between S eas and Ca using a weighted linear regression model.  

Once again, as you work through this example, remember that x represents the concentration of analyte in the standards (Cs), and y corresponds to the average signal (Smeas)- We begin by setting up a table to aid in the calculation of the weighting factor.  

Adding together the values in the forth column gives 

After the individual weights have been calculated, a second table is used to aid in calculating the four summation terms in equations 5.22 and 5.23. 

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CA Weighted Linear Regression with Errors in Both x andy... 

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