Computational Linear Algebra & Statistics for Computer Science

Catalog description

This course consists of three components: linear algebra including linear equations and matrices, vector spaces, subspaces, linear independence, bases, dimension, linear transformations, eigenvalues/eigenvectors, and diagonalization; Operations research including linear programming and the simplex method; Statistical inference including point and interval estimation, bias, hypothesis testing, linear models (encompassing regression and ANOVA). Enrollment restricted to Computer Science students or by approval of Department Chair. Not open to students with credit in (MATH 272 or MATH 372 or MATH 336 ).A grade of C or better in Calculus II ( MATH 156 or MATH 186 or MATH 188 ). Fall.