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Terminology: matrix minors and cofactors (involves Cramer's rule)

Background

I'm reading Karl Pearson's 1900 paper titled:

On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling

I paraphrase the opening. He supposes $x_1, x_2, \ldots, x_n$ is a system of random variables following a multivariate normal distribution centered at the origin. Then he asserts the probability density of the vector $\langle x_1, x_2, \ldots, x_n \rangle$ is $$ Z = Z_0 \exp\left( -\frac{1}{2\det S}\sum_i \sum_j S_{pq} x_p x_q\right)\,, $$ where

  • $S$ is the covariance matrix of $x_1, x_2, \ldots, x_n$
  • $S_{pq}$ is the "minor obtained by striking out the $p$th row and $q$th column" of the covariance matrix
  • $Z_0$ is an unspecified constant.

This appears inconsistent with the multivariate normal density function from Wikipedia, which involves a matrix inverse. These two expressions for the density function can be reconciled using Cramer's rule, but only if what Karl Pearson meant by "minor" is what we today would call a "cofactor."

Question

In 1900, did the word "minor" refer to what we would call a "cofactor"?