Math 221: Introductory Linear Algebra topics covered in the course include the solution of systems of linear equations through Gaussian elimination; matrices and matrix algebra; vector spaces and their subspaces; coordinate mappings and other linear transformations; eigenvalues and eigenvectors; similarity and diagonalization; and constructions involving inner products such as orthogonal projections, the construction of Gram-Schmidt bases and least-square approximations. Although the course devotes a substantial amount of time to computational techniques, it should also lead the student to develop geometrical intuitions, to appreciate and understand mathematical abstraction, and to construct some elementary proofs.
Prerequisites: Math 100 or equivalent. A grade of 'C' or better is required.
Accessibility Services Notice
standard statementCourse Details| Total number of weeks | 15 |
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| Total Credits | |
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| Total Hours | 75 |
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Typical hours per week breakdown| Lecture | 3 |
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| Lab (lab, field, computer) | 2 |
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Outcomes
Upon successful completion of this course, the learner will be able to:
- apply Gaussian elimination, rank-nullity theorem, fundamental theorem of linear algebra, diagonalization algorithm, subspace test, coordinate transformations, row space algorithm, casting-out algorithm, Gram-Schmidt bases, and least-square approximations ;
- define terms and concepts found in linear algebra;
- classify necessary and sufficient conditions for diagonalization, linear independence and dependence, subspaces, and matrix invertibility;
- construct elementary proofs;
- analyze parametric and vector equations and provide geometric descriptions for solutions to systems of linear equations; and
- provide geometric descriptions for the kernel and image of linear transformations.
Grading Table
Academic and Career
See the Academic Calendar for General Information including how to withdraw from course(s) and other regulations.
Disclaimer
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