ABSTRACT
We previously considered a few techniques for fitting curves to data: (1) linear regression, (2) nonlinear regression, and (3) kernel smoothing. These methods allowed us to draw a best-fit line through a set of data. We will now address the uncertainties of best-fit lines for cases where linear regression is used. The focus of this chapter will be on using a Taylor series approach. Monte Carlo methods [1], which can readily be used for nonlinear regression and kernel smoothing approaches, will be discussed in the next chapter.
