Introduction -- General background material -- Geometric and analytic properties of the Moore-Penrose pseudoinverse -- Pseudoinverses of partioned matrices and sums and products of matrices -- Computational methods -- The general linear hypothesis -- Constrained least squares, penalty functions, and BLUE's -- Recursive computation of least squares estimators -- Nonnegative definite matrices, conditional expectation, and Kalman filtering.