Studies in the History of Probability and Statistics. XV The historical development of the Gauss linear model

Abstract

The linear regression model owes so much to Gauss that we believe it should bear his name. Other authors who made substantial contributions are: Cauchy who introduced the idea of orthogonality; Chebyshev who applied it to polynomial models; Pizzetti who found the distribution of the sum of squares of the residuals on the Normal assumption; Karl Pearson who linked the model with the multivariate Normal thereby broadening the field of applications; and R. A. Fisher whose extension of orthogonality to qualitative comparisons laid the foundations of the modern theory of experimental design.

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