The history of this goes back to Gauss (1809, 1823), who in his study of the motion of the planets developed methods for the weighted combination of observations with errors. We will approach it from a Bayesian standpoint, following Lorenc (1986) and Lorenc and Hammon (1988). The Bayesian formalism gives a consistent treatment allowing for the (unfortunately common) occurrence of observations with "gross" errors. The resulting equations are equivalent to Gauss's minimum variance approach, for observations with a Gaussian error distribution.