Carl Meyer

      Advanced Analytics 502: Linear Algebra

      Module Outline --- by section number in the text book


Pre-Course Tutorial

1.2 Gaussian Elimination And Matrices

1.3 Gauss-Jordan Method

Pre-Course Tutorial

2.1 & 2.2 Row Echelon Forms And Rank

2.4 & 2.5 Homogeneous & Nonhomogeneous Systems

Pre-Course Tutorial

3.2, 3.5, 3.6, 3.7 Basic Matrix Algebra

3.9, 3.10 Elementary Matrices And The LU Factorization

Lesson 1

4.1 Spaces And Subspaces

4.2 Four Fundamental Subspaces

Lesson 2

4.3 Linear Independence

4.4 Basis And Dimension

Lesson 3

4.6 Least Squares (classical)

5.13 Least Squares (geometrical) and projections

Lesson 4

5.1 & 5.2 Norms and Standard Inner Product

5.4 Orthogonal Vectors and Fourier Expansion

Lesson 5

5.4.3 Linear Correlation

7.1 Introduction to Eigenvalues

On Your Own Time

6.1 & 6.2 Determinants

(Review As You Feel You Need To)

Lesson 6

7.1 More Properties Of Eigensystems

7.2 Diagonalization by Similarity Transformations

Lesson 7

7.6 Positive Definite Matrices

5.12 Singular Value Decomposition

Lesson 8

Exam Day

Exam Problems From The Homework Assignments