Math 317  Theory of Linear Algebra  Sections 2 and 3
Instructor: Jonas Hartwig jth@iastate.edu Office: Carver 470, office hours TF 34.
TA/Grader: Issac Odegard. Office 477, office hour W 23.
Course Log and Homework Assignments
Click here for a list of recommended practice problems.
Aug 2630: §1.1, §4.1, §1.2. HW: §1.1 #11,20,22a
Sep 26: §1.4, §1.5, §2.1. HW: §1.2: #8,10; §1.4: #6,13b
Sep 913: §2.2, §2.3, §2.4. HW: §1.5: #28ab; §2.1: #5
Sep 1620: §2.4, §3.1, §3.2. HW: §2.2: #9,11a; §2.3: #8b; §2.4: #7b,14bc
Sep 2327: Thursday Exam 1 on Ch.1 & Ch.2 HW: §3.1: #5b,9b,11b; §3.2: #2d,5,7
Sep 30Oct 4:
Oct 711:
Oct 1418:
Oct 2125:
Oct 28Nov 1: Thursday Exam 2 on Ch.3 & Ch. 4
Nov 48:
Nov 1115:
Nov 1822: Thursday Exam 3 on Ch.5
Nov 2529: Thanksgiving break
Dec 26:
Dec 913:
Dec 1620: Finals week
Final Exam
MATH 317 Section 2: Thursday December 19 at 12:00 PM
MATH 317 Section 3: Tuesday December 17 at 2:15 PM
Catalog Description
MATH 317. Theory of Linear Algebra.
(40) Cr. 4. F.S.SS. Credit or enrollment in MATH 201
Systems of linear equations, determinants, vector spaces, inner product spaces, linear transformations, eigenvalues and eigenvectors.
Emphasis on writing proofs and results. Only one of MATH 207 and MATH 317 may be counted toward graduation.
Textbook
Andrilli and Hecker
Elementary Linear Algebra
5th Edition
ISBN: 9780128008539
Syllabus
Chapter 1: Vectors and Matrices (6 lectures)
Chapter 2: Systems of Linear Equations (7 lectures)
Chapter 3: Determinants and Eigenvalues (8 lectures)
Chapter 4: FiniteDimensional Vector Spaces (16 lectures)
Chapter 5: Linear Transformations (15 lectures)
Chapter 6: Orthogonality (7 lectures)
Grading
Homework: 20%
Inclass activities: 15%
Exams 13: 15% each
Final: 20%
Objectives for Math 317
Be able to:
 use vector algebra, matrix algebra and dot products to manipulate vector and matrix equations.
 find the solution set to a given linear system of equations in parametric form.
 compute the echelon and reduced echelon forms of a matrix .
 compute row space, column space, null space, left null space, rank of a matrix.
 compute inverse matrices.
 compute orthogonal projections on to vectors and hyperplanes.
 compute determinants, and understand the basic properties of determinants.
 compute orthogonal complements of a subspace
 determine the dimension of a vector subspace
 compute the standard matrix for a given linear transformation.
 compute the matrix for a linear transformation with respect to a given basis.
 compute an orthogonal basis from one that is not orthogonal.
 find an orthogonal matrix that diagonalizes a given symmetric matrix.

Be able to prove simple theorems on fundamental properties of linear algebra. These could include the following.
 Prove a given set is a subspace (or prove it is not).
 Prove a given set of vectors is linearly independent (or prove it is not).
 Prove a given transformation is linear (or is not).
 Use key theorems such as the Dimension Theorem to deduce properties of a given linear transformation.
 Prove whether a set of vectors forms a basis.

Old Exams
Sample Final
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