MATH-111(e): Linear Algebra

Lectures in this course (136)

Covers the basics of matrix inversion, properties of matrix multiplication, and the uniqueness of matrix inverses.

Explains how to find the values for which -1 is an eigenvalue of a 3 by 3 matrix.

Covers characteristic polynomials, similar matrices, eigenvalues, and algebraic multiplicities.

Introduces abstract concepts in linear algebra, focusing on operations with vectors and matrices.

Discusses the misconception that an injective linear map must have M strictly smaller than N.

Explores matrix similarity, eigenvalues, and diagonalization in linear algebra.

Covers the basics of linear algebra, emphasizing the identification of subspaces through key properties.

Focuses on finding eigenvalues and eigenvectors of a matrix, emphasizing attention to detail in linear algebra problems.

Explores the relationship between similar matrices and their eigenvalues.

Discusses properties of symmetric matrices and the Spectral Theorem.

Covers the theory and examples of diagonalizing matrices, focusing on eigenvalues, eigenvectors, and linear independence.

Explores diagonalization of matrices, conditions, invertibility, rank, nullity, and eigenvectors.

Covers linear transformations between polynomial spaces and explores examples of linear independence and bases.

Explains how the inverse of a matrix shares its eigenvalue and how the transposed version has the same set of eigenvalues.

Covers the concept of diagonalization of matrices through the study of eigenvectors and eigenvalues.

Covers the diagonalization of matrices, showing how to find a basis for diagonal matrices.

Explores matrix similarity and diagonalization rules, emphasizing eigenvectors and distinct eigenvalues.

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