Linear Algebra Review Notes
Course notes are downloadable pdfs that are available for purchase. They are completed versions of the guided notes which can be viewed here.
Course notes are detailed, handcrafted and provide clear explanations, step by step problem solving strategies, and worked out example problems.
1: Linear Equations
Solutions to a Linear System with Two Equations and Two Unknowns
Coefficient and Augmented Matrices
Elementary Row Operations, Echelon, and Reduced Echelon Form
Gaussian Elimination and Gauss Jordan Elimination
Consistent and Inconsistent Linear Systems
Linear Combinations and Span
2: Matrix Algebra
Addition, Subtraction, and Multiplication of Matrices
Transpose and Trace of a Matrix
Special Matrices - Triangular, Symmetric, and Diagonal
Inverse of a 2x2 and 3x3 Matrix
Solutions to a Linear System Using Matrix Inversion
3: Transformations
Linear Transformations - Domain and Codomain
Linear Transformations - Standard Matrix
Matrix Transformations - Reflection, Projection, Rotation
One-To-One and Onto Transformations
4: Determinants
Determinant of a 2x2 Matrix
Determinant of a 3x3 Matrix - Cofactor Expansion, Shortcut, Row Reduction
Properties of Determinants
Cramer’s Rule
5: Vector Spaces
Linear Independence
Basis
Coordinate Vectors
Dimension
Row Space, Column Space, and Null Space
Rank of a Matrix and Rank Theorem
6: Eigenvalues and Eigenvectors
Introduction to Eigenvalues and Eigenvectors
How to Find Eigenvalues
How to Find Eigenvectors and a Basis for an Eigenspace
Similar Matrices
Diagonalization
Complex Eigenvalues and Eigenvectors
7: Orthogonality
Norm of a Vector, Unit Vector, Standard Unit Vector
Distance in R^n
Dot Product
Orthogonality of Vectors
Orthogonal Projection
Linear Combination of Orthogonal Vectors
Gram Schmidt Process
Orthogonal Matrices
Orthogonal Diagonalization
Course notes are downloadable pdfs that are available for purchase. They are completed versions of the guided notes which can be viewed here.
Course notes are detailed, handcrafted and provide clear explanations, step by step problem solving strategies, and worked out example problems.
1: Linear Equations
Solutions to a Linear System with Two Equations and Two Unknowns
Coefficient and Augmented Matrices
Elementary Row Operations, Echelon, and Reduced Echelon Form
Gaussian Elimination and Gauss Jordan Elimination
Consistent and Inconsistent Linear Systems
Linear Combinations and Span
2: Matrix Algebra
Addition, Subtraction, and Multiplication of Matrices
Transpose and Trace of a Matrix
Special Matrices - Triangular, Symmetric, and Diagonal
Inverse of a 2x2 and 3x3 Matrix
Solutions to a Linear System Using Matrix Inversion
3: Transformations
Linear Transformations - Domain and Codomain
Linear Transformations - Standard Matrix
Matrix Transformations - Reflection, Projection, Rotation
One-To-One and Onto Transformations
4: Determinants
Determinant of a 2x2 Matrix
Determinant of a 3x3 Matrix - Cofactor Expansion, Shortcut, Row Reduction
Properties of Determinants
Cramer’s Rule
5: Vector Spaces
Linear Independence
Basis
Coordinate Vectors
Dimension
Row Space, Column Space, and Null Space
Rank of a Matrix and Rank Theorem
6: Eigenvalues and Eigenvectors
Introduction to Eigenvalues and Eigenvectors
How to Find Eigenvalues
How to Find Eigenvectors and a Basis for an Eigenspace
Similar Matrices
Diagonalization
Complex Eigenvalues and Eigenvectors
7: Orthogonality
Norm of a Vector, Unit Vector, Standard Unit Vector
Distance in R^n
Dot Product
Orthogonality of Vectors
Orthogonal Projection
Linear Combination of Orthogonal Vectors
Gram Schmidt Process
Orthogonal Matrices
Orthogonal Diagonalization
Course notes are downloadable pdfs that are available for purchase. They are completed versions of the guided notes which can be viewed here.
Course notes are detailed, handcrafted and provide clear explanations, step by step problem solving strategies, and worked out example problems.
1: Linear Equations
Solutions to a Linear System with Two Equations and Two Unknowns
Coefficient and Augmented Matrices
Elementary Row Operations, Echelon, and Reduced Echelon Form
Gaussian Elimination and Gauss Jordan Elimination
Consistent and Inconsistent Linear Systems
Linear Combinations and Span
2: Matrix Algebra
Addition, Subtraction, and Multiplication of Matrices
Transpose and Trace of a Matrix
Special Matrices - Triangular, Symmetric, and Diagonal
Inverse of a 2x2 and 3x3 Matrix
Solutions to a Linear System Using Matrix Inversion
3: Transformations
Linear Transformations - Domain and Codomain
Linear Transformations - Standard Matrix
Matrix Transformations - Reflection, Projection, Rotation
One-To-One and Onto Transformations
4: Determinants
Determinant of a 2x2 Matrix
Determinant of a 3x3 Matrix - Cofactor Expansion, Shortcut, Row Reduction
Properties of Determinants
Cramer’s Rule
5: Vector Spaces
Linear Independence
Basis
Coordinate Vectors
Dimension
Row Space, Column Space, and Null Space
Rank of a Matrix and Rank Theorem
6: Eigenvalues and Eigenvectors
Introduction to Eigenvalues and Eigenvectors
How to Find Eigenvalues
How to Find Eigenvectors and a Basis for an Eigenspace
Similar Matrices
Diagonalization
Complex Eigenvalues and Eigenvectors
7: Orthogonality
Norm of a Vector, Unit Vector, Standard Unit Vector
Distance in R^n
Dot Product
Orthogonality of Vectors
Orthogonal Projection
Linear Combination of Orthogonal Vectors
Gram Schmidt Process
Orthogonal Matrices
Orthogonal Diagonalization