Chapter 3 Videos

3.2 Matrix Addition and Subtraction

3.2S1 - Stata - Addition and Subtraction

3.3 Scalar Multiplication

3.3S1 - Stata - Scalar Multiplication

3.4 Transpose of a Matrix

3.4S1 - Stata - Transpose of a Matrix

3.5 Simple Matrix Multiplication

3.5S1 - Stata - Simple Matrix Multiplication

3.6 Matrix Multiplication

3.6S1 - Stata - Matrix Multiplication

3.7 Multiplying a Vector by its Transpose (Dot Products and Matrix Products)

3.7S1 - Stata - Multiplying a Vector by its Transpose (Dot Products and matrix Products)

3.8 CSSCP Matrix

3.8S1 - Stata - CSSCP Matrix

3.9.1 Division by a Scalar - prereq: video 3.6

3.9.1S1 - Stata - Division by a Scalar - This is a supplement to video 3.9.1

3.9.2 Getting a Covariance Matrix - prereq: video 3.9.1

3.9.2S1 - Stata - Getting a Covariance Matrix - This is a supplement to video 3.9.2

3.10 Symmetric Martix - prereq: video 3.6

3.10S1 - Stata - Symmetric Matrix - This is a supplement to video 3.10

3.11 Diagonal Matrix - prereq: video 3.6

3.11S1 - Stata - Diagonal Matrix - This is a supplement to video 3.11

3.12 Standardizing and Correlation Matrices - prereqs: videos 3.9.2, 3.11

3.12S1 - Stata - Standardizing and Correlation Matrices - This is a supplement to video 3.12

3.13 Identity Matrix - prereq: video 3.6

3.14 J Matrix - prereq: video 3.6

3.15 Using a J Matrix to Create Deviation Scores - prereqs: videos 3.2, 3.14

3.15S1 - Stata - Using a J Matrix to Create Deviation Scores - This is a supplement to video 3.15

3.16 Centering Matrix - prereq: video 3.15

3.16S1 - Stata - Cenering Matrix - This is a supplement to video 3.16

3.17 Idempotent Matrix - prereq: video 3.16

3.17S1 - Stata - Idempotent Matrix - This is a supplement to video 3.18

3.18 Obtaining Covariance Matrices Using I and J - prereqs: Chapter 2 pp. 31-33; videos 3.8, 3.17

3.18S1 - Stata - Obtaining Covariance Matrices Using I and J - This is a supplement to video 3.18

3.19 Summary of Principles to Cov and Corr Matrices - prereqs: videos 3.12, 3.18

3.20 Relevance to Geometry and Pythagorean Theorem

3.21 Adjoined Matrices
- prereq: video 3.3

3.21S1 - Stata - Adjoined Matrices
- This is a supplement to video 3.21

3.22 Partitioned Matrices
- prereqs: videos 3.4, 3.6, 3.21

3.23 Triangular Square Root Matrices
- prereqs: videos 3.4, 3.6

3.23S1 - Stata - Triangular Square Root Matrices
- This is a supplement to video 3.23

3.24 Determinants

3.24S1 - Stata - Determinants

3.25 The Bent Diagonals Method
- prereq: video 3.24

3.26 The Matrix Extension Method
- prereq: video 3.24

3.27 The Method of Cofactors
- prereq: video 3.24

3.28 The Trace and the Determinant of a Covariace Matrix
- prereqs: videos 3.20, 3.24

3.28s Continuation of 3.28
- This is a continuation of video 3.28

3.28S1 - Stata - The Trace of a Covariance Matrix
- This is a supplement to video 3.28

3.29 Introduction to Matrix Inversion
- prereqs: videos 3.13, 3.24

3.29S1 - Stata - Matrix Inversion
- This is a supplement to video 3.29

3.30 Matrix Inversion by the Method of Cofactors
- prereqs: videos 3.6, 3.21, 3.26, 3.27, 3.29

3.31 Matrix Inversion by the Cholesky Method
- prereqs: videos 3.23, 3.30

3.32 Rank of a Matrix
- prereq: video 3.24

3.33 Orthogonal Vectors and Matrices
- prereq: video 3.6

3.33S1 - Stata - Orthogonal Vectors and Matrices
- This is a supplement to video 3.33

3.34 Quadratic Forms
- prereqs: videos 3.9, 3.18

3.35 Bilinear Forms- prereq: video 3.34

3.36 Covariance Matrix Transformation (*not yet available*)
- prereq: video 3.35

3.37 Eigenvectors and Eigenvalues
- prereqs: videos 3.6, 3.32

3.37S1 - Stata - Eigenvectors and Eigenvalues
- This is a supplement to video 3.37

3.38 Spectral Decomposition
- prereqs: videos 3.30, 3.37

3.39 Triangular Decomposition
- prereqs: videos 3.23, 3.38

3.40 Normalization of a Vector
- prereq: video 3.1