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. Show more.