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This document tests your knowledge on various concepts in linear algebra, including matrix manipulations, vector spaces, and eigenvalues. Topics covered include matrix addition, multiplication, and transposition, linear independence, span, basis, dimension, rank, determinants, inverse matrices, and eigenvalues. Questions also cover homogeneous and non-homogeneous linear systems, and finding eigenvectors and eigenvalues.
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□ Are you comfortable with the following matrix manipulations?
□ Do you know the definition of linear independence of a set of vectors?
□ Do you know what a vector space is? Do you know how to decide whether a subset of a given vector space is a subspace (i.e. is itself a vector space)?
□ Do you know what the span of a set of vectors is?
□ Do you know what a basis is? Given a set of vectors, do you know how to decide whether the vectors in the set form a basis of a given vector space?
□ Do you know how to find the dimension of a vector space? In particular, do you know how to find the dimensions of the column space, of the row space, and of the null space of a matrix?
□ How is the rank of a matrix defined?
□ Do you know what the rank theorem says?
□ What is a linear system of equations?
□ Do you know how to decide whether a linear system of equations is consistent?
□ If a system is consistent, how do you know whether it has just one or an infinite number of solutions?
□ What does it mean for a linear system of equations to be homogeneous? What is the form of the general solution to a non-homogeneous linear system of equations?
□ Do you know how to find the inverse of a square matrix?
□ Do you know how to expand a determinant with respect to one of its columns or one of its rows?
□ Do you know what happens to a determinant if you multiply one row by a constant? What if you multiply 2 rows by the same constant? What if instead of rows, you multiply some of the columns by a constant?
□ What are the typical manipulations needed to calculate a determinant?
□ Is the inverse of a product of matrices equal to the product of their inverses?
□ How does one calculate the inverse of a 2 by 2 matrix?
□ What does it mean for a matrix to be singular?
□ What is the general method for finding the eigenvalues of a matrix? Is there a “shortcut” if the matrix is 2 by 2? If so, what is it?
□ How does one find an eigenvector of a matrix A?
□ What are the algebraic and geometric multiplicities of an eigenvalue? Are they always the same?
□ What is an eigenspace? How does one find its dimension?
□ What is a generalized eigenvector?
□ Sometimes it is possible to find an eigenvector just by looking at a matrix. When does this occur? Why?
□ Under what conditions on a matrix A are the eigenvalues of A equal to the diagonal entries of A?