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The wikipedia pages on Auguste Bravais,Karl Pearson, the Pearson correlation coefficient,and Francis Galton all cite the following book:

Bravais, A (1846). "Analyse mathématique sur les probabilités des erreurs de situation d'un point" [Mathematical analysis of the probabilities of errors in a point's location]. Mémoires Presents Par Divers Savants à l'Académie des Sciences de l'Institut de France. Sciences Mathématiques et Physiques. 9: 255–332.

Piovani 2007 cites Pearson 1896 and Yule 1909 as claiming that Bravais 1846 was the first discussion of correlation:

"Pearson (1896: 261) offers one of the earliest reconstructions of the origins of cor- relation, singling out the essay, Analyse Mathématique sur les Probabilités des Erreurs de Situation d’un Point by Bravais (1846) as the place where the notion was first discussed."

"The fundamental theorems of correlation were for the first time and almost exhaustively discussed by Bravais [...] He deals completely with the correlation of two and three variables [...] The ‘Galton’s function’ or coefficient of correla- tion [...] indeed appears in Bravais’ work, but a single symbol is not used for it (Pearson 1896: 261)."

Of the numerous memoirs on the theory of error the most important in [...] connection [to correlation] is that of A. Bravais, who as long ago as 1846 discussed the theory of error for points in space, regarding the errors as either independent or correlated, from the standpoint of the normal law of errors. He did not, however, use a single symbol for a correlation coefficient, although the product-sum formula may be regarded as due to him (Yule 1909: 722).

In Sewall Wright's "Correlation and Causation" (1921), where he introduces his method of path coefficients, he claims that Bravais developed the equation first.

The formula for what Galton later called the coefficient of correlation was, in fact, first presented in this connection by Bravais (I) in 1846.

Purportedly it was in this book that Bravais derived the correlation coefficient, but going through the pages of the book I did not see the equation in its modern form. That could be due to limitations of the translation tool combined with not being able to read French, but I would like to confirm from the original document where he worked out the equation.

Galen
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    Based on a very quick glance through this monograph, I believe Bravais first developed the theory of the multivariate Normal distribution--in which the covariance matrix plays a starring role--and then derived the (multivariate!) OLS Normal equations and solved them. Most of this is a matter of algebra and some geometry, all of which he carried out without the benefit of matrix notation. He explicitly stated his work applied to $n$ variables, but illustrated the calculations only for up to $n=4$ variables (to show how the general case goes). For its time it appears to be a tour de force. – whuber Jun 24 '21 at 13:32
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    The correlation coefficient appears to show up in disguise as $T,$ the angle formed between the regression line and a major axis: compare the figure on p. 19 to some of my graphics near the end of my post at https://stats.stackexchange.com/a/71303/919. BTW, we can also find the $\chi^2(2)$ distribution derived (at eq. 34) explicitly as a formula for the tail area of a quadratic form. – whuber Jun 24 '21 at 13:39

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