least squares approximation | least squares approximations

A mathematical procedure for finding the best-fitting curve to a given set of points by minimizing the sum of the curve's squared offsets from the data.

A mathematical procedure for finding the best-fitting curve to a given set of points by minimizing the sum of the squares of the offsets ("the residuals") of the points from the curve. The sum of the squares of the offsets is used instead of the offset absolute values because this allows the residuals to be treated as a continuous differentiable quantity. However, because squares of the offsets are used, outlying points can have a disproportionate effect on the fit, a property which may or may not be desirable depending on the problem at hand.

ANOVA | correlation coefficient | interpolation | least squares fitting--exponential | least squares fitting--logarithmic | least squares fitting--perpendicular offsets | least squares fitting--polynomial | least squares fitting--power law | MANOVA | matrix 1-inverse | Moore-Penrose matrix inverse | nonlinear least squares fitting | pseudoinverse | regression coefficient | residual | spline

college level (AP statistics)