Since there are C(m,k) choices of k rows out of m, and there are C('\'n,k) choices of k columns out of n, there are a total of C(m,k)C(n,k) minors of size k×k''.
Especially important are the (n-1)×(n-1) minors of an n×n square matrix - these are often denoted Mij, and are derived by removing the ith row and the jth column.
The cofactors of a square matrix A are closely related to the minors of A: the cofactor Cij of A is defined as (-1)i+j times the minor Mij of A.
For example, given the matrix
Given an m×n matrix with real entries (or entries from any other field) and rank r, then there exists at least one non-zero r×r minor, while all larger minors are zero.
We will use the following notation for minors: if A is an m×n matrix, I is a subset of {1,...,m} with k elements and J is a subset of {1,...,n} with k elements, then we write [A]I,J for the k×k minor of A that corresponds to the rows with index in I and the columns with index in J.
Both the formula for ordinary matrix multiplication and the Cauchy-Binet formula for the determinant of the product of two matrices are special cases of the following general statement about the minors of a product of two matrices. Suppose that A is an m×n matrix, B is an n×p matrix, I is a subset of {1,...,m} with k elements and J is a subset of {1,...,p} with k elements. Then
A more systematic, algebraic treatment of the minor concept is given in multilinear algebra, using the wedge product. If the columns of a matrix are wedged together k at a time, the kxk minors appear as the components of the resulting k-vectors.