## Background

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

[*On the Criterion that a given System of Deviations from the Probably in the Case of a Correlated System of Variables is such that it can be reasonably supposed to have arisen from Random Sampling*][1]

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][2], 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"?


  [1]: http://www.medicine.mcgill.ca/epidemiology/hanley/bios601/Proportion/Pearson1900.pdf
  [2]: https://en.wikipedia.org/wiki/Multivariate_normal_distribution#Density_function