Least Squares Methods for Treating Problems with Uncertainty in x and y

Methods for straight-line fitting of data having uncertainty in x and y are compared through Monte Carlo simulations and application to specific data sets. Under special circumstances, the "ignorance" methods, methods which are typically used without information about the data errors σ and σ, are equivalent to the recommended best approach. The latter is numerical rather than formulaic but is easy to implement in programs that permit user-defined fit functions. It can handle any response function, linear or nonlinear, for any σ and σ. Estimates for the latter must be supplied and rightfully belong in any data analysis.