Catalog 2016-2017 
    Mar 21, 2018  
Catalog 2016-2017 [ARCHIVED CATALOG]

MATH 230 Matrix Algebra with Applications

5 credits
This course serves as an introduction to matrix theory and linear algebra. Topics covered include: systems of equations, Gaussian elimination, LU decomposition, Euclidean vector spaces and subpaces, linear transformations, basis sets and dimensions, span of a vector space, Gram-Schmidt orthogonalization, least squares methods, eigenvalues and eigenvectors. Applications are emphasized.

Prerequisites: MATH& 163  

Quarters Offered: Spring

Student Outcomes/Competencies:
Upon successful completion of this course students will be able to:

  • Perform matrix operations, calculate determinants, find inverses for matrices (where possible), and find the transpose of a matrix
  • Use elementary row operations to solve systems of linear equations using Gaussian Elimination and Gauss-Jordan reduction methods
  • Apply LU decomposition methods to factorize a matrix
  • Identify a system of linear equations as independent, inconsistent, or dependent
  • Identify properties of Euclidean vector spaces and the effects of linear transformations
  • Perform vector operations; use properties of vector operations; and determine vector subspaces, spanning sets, and bases of vector spaces
  • Show that a set of vectors forms the basis for a set, and find the dimension of a subspace
  • Find inner products and find a basis for a given inner product space
  • Use matrices to perform transformations between vector spaces and to identify isomorphisms
  • Find the kernel, range, rank, and nullity of a linear transformation
  • Find the standard matrix for a given linear transformation and use this matrix to find the image of a given vector
  • Use Gram-Schmidt orthogonalization to find orthonormal vectors
  • Apply QR decomposition methods to factorize a matrix
  • Find real eigenvalues and eigenvectors of a square matrix
  • Diagonalize symmetric matrices
  • Apply matrix algebra to data fitting and least squares analysis
  • Use the mathematical critical thinking skills of problem solving, pattern recognition, substitution, following structural rules, and quantitative modeling to solve problems requiring reasoning, critical thinking, and computation