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==Ordinary and weighted least squares==
The best-fit curve is often assumed to be that which minimizes the sum of squared [[errors and residuals in statistics|residuals]]. This is the [[ordinary least squares]] (OLS) approach. However, in cases where the dependent variable does not have constant variance, or there are some outliers, a sum of weighted squared residuals may be minimized; see [[weighted least squares]]. Each weight should ideally be equal to the reciprocal of the variance of the observation, or the reciprocal of the dependent variable to some power in the outlier case, but weights may be recomputed on each iteration, in an iteratively weighted least squares algorithm.
==Linearization==
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