Mathematics

# MATH 2331: Linear Algebra

Lecture - 4 credits

ND

EI

IC

FQ

SI

AD

DD

ER

WF

WD

WI

EX

CE

- Uses the Gauss-Jordan elimination algorithm to analyze and find bases for subspaces such as the image and kernel of a linear transformation.
- Covers the geometry of linear transformations: orthogonality, the Gram-Schmidt process, rotation matrices, and least squares fit.
- Examines diagonalization and similarity, and the spectral theorem and the singular value decomposition.
- Is primarily for math and science majors; applications are drawn from many technical fields.
- Computation is aided by the use of software such as Maple or MATLAB, and graphing calculators.

Uses the Gauss-Jordan elimination algorithm to analyze and find bases for subspaces such as the image and kernel of a linear transformation.

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