|
| Assignment | |
|---|---|---|
| 1.1 | 10 | |
| 1.2 | 25 | |
| 1.3 | 36 | |
| 1.4 | 46 | |
| 1.5 | 55 | |
| 1.6 | 64 | |
| 1.7 | 73 | |
| 1.8* | 83 | |
| 2.1 | 107 | |
| 2.2 | 117 | |
| 2.3 | 123 | |
| 2.4* | 130 | |
| 2.5* | 139 | |
| 2.7@ | 153 | |
| 2.8@ | 163 | |
| 2.9* | 174 | |
| 3.1* | 185 | |
| 3.2* | 193 | |
| 4.1 | 217 | |
| 4.2 | 228 | |
| 4.3 | 237 | |
| 4.4 | 248 | |
| 4.5 | 255 | |
| 4.6 | 263 | |
| 4.7* | 270 | |
| 4.9@ | 290 | |
| 5.1 | 302 | |
| 5.2 | 311 | |
| 5.3 | 319 | |
| 5.4* | 327 | |
| 5.5* | 335 | |
| 5.6@ | 346 | |
| 6.1 | 376 | |
| 6.2 | 386 | |
| 6.3 | 395 | |
| 6.4* | 402 | |
| 6.5 | 411 | |
| 6.6@ | 420 | |
| 7.1 | 448 | |
| 7.2 | 457 | |
| 7.3* | 465 |
MATH260 is a linear algebra (sometimes called matrix theory) course. Topic include systems of linear equations, row reduction, applications of linear systems, vectors in 3-space, linear independence, linear transformation, matrix operations, computer graphics@, determinants*, vector spaces , null space, column and row space, basis, eigenvectors, eigenvalues, diagonalization, complex eigenvalues*, inner product, length, orthogonality and orthogonal projections, Gram-Schmidt process*, least-squares problems, and quadratic forms.