F^n is a vector space.
For invertible linear transformations A and B
For matrices
Formula for computing the least squares solution to a linear system
Formula for computing the least squares solution to a linear system.
Formula for diagonalizing a real 2-by-2 matrix with a complex eigenvalue.
Formula for the coordinates of a vector with respect to an orthogonal/orthonormal basis.
Formula for the coordinates of the projection of a vector onto a subspace
Formula for the determinant of a 2-by-2 matrix.
Formula for the determinant of a 3-by-3 matrix.
Formula for the inverse of a 2-by-2 matrix.
Formula for the least-squares linear fit to 2-dimensional data
Formula for the (orthogonal) projection of one vector onto another vector
Formula for the spectral decomposition for a symmetric matrix
For n-by-n invertible matrices A and B
Gaussian elimination as a method to solve a linear system
Gauss-Jordan procedure to put a matrix into reduced row echelon form
Geometric description of span of a set of vectors in R^n (or C^n)
Geometric picture of a 2-by-2 linear system
Geometric picture of a 3-by-3 linear system
Geometric picture of the solution set of a linear equation in 3 unknowns
Geometric properties of linear transformations
Geometric properties of linear transformations on R^2
Geometric properties of R^n (or C^n)
Hermitian matrices

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