ORTHOGONALITY AND LEAST SQUARES
Orthogonal Vectors Norm Unit Vector Orthonormal Vectors Orthogonal Complement Orthogonal Projection Cauchy-Schwarz Inequality Angle Between Two Vectors Gram-Schmidt Process QR Factorialization Transpose Symmetric and Skew-symmetric Matrices Orthogonal Matrices Least Squares Solutions Matrix of an Orthogonal Projection	Please click on a topic in the left margin to view helpful MATLAB instructions, examples, and exercises. This chapter introduces orthonormal bases and the Gram-Schmidt process, along with the QR factorialization and the important technique of least-squares approximation.