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Math Department



Last modified:
7 July 2004

Linear Algebra

Course Info:

This is a course info page for Math 250 section B7. I will try to post the hand-in homework assignments here. The text for the course is Elementary Linear Algebra: A Matrix Approach by Spence, Insel & Friedberg.

The course meets MWF from 6:15 to 9 PM in Beck 111 on Livingston Campus.

Contact Info:

Instructor: Brian Lins
Office: Room 618, Hill Center, Busch Campus
Office Hours: Fridays 4:00-5:00 PM and Tuesdays 2:00-3:00 PM. Also by appointment.
E-mail Address: bclins (at) math

Review Problems

Grading

You should be able to find your grades in a week or so at www.acs.rutgers.edu/grades

The grading break down of the course will be as follows. Note: I will drop the lowest one quiz grade and two homework grades from the final totals.

Grades Value
Homework
100 points total
Quizzes
100 points total
Midterm Exam #1
100 points
Midterm Exam #2
100 points
Final Exam
200 points


Homework Assignments

These are the assigned homework problems and will be due during the class period immediately following the one in which they were assigned. In addition to these required problems, a list of practice problems can be found as a pdf file here . These practice problems are recommended but not required.

Homework Date Assigned Problems
1
6/2
sec 1.2# 2, 9; sec 1.3# 4, 30, 36; sec 1.4# 8
2
6/7
sec 1.6# 28, 40; sec 1.7# 12, 24; sec 2.1# 42
3
6/9
sec 2.3# 16, 22; sec 2.4# 7, 10, 19
4
6/16
sec 3.1# 20, 26, 30, 46; sec 3.2# 19, 38
5
6/21
sec 5.1# 12, 21, 45; sec 5.2# 22
6
6/23
sec 5.2# 17; sec 5.3# 12, 21, 34, 45
7
6/28
sec 6.1# 6, 12, 14, 32; sec 6.2# 4, 16
8
6/30
sec 6.2# 11, 19, 23; sec 6.3# 5, 13


Tentative Syllabus

Lecture Date Sections Topics
1
6/2
1.1, 1.2, 1.3
Matrices & Vectors; Systems of Linear Equations
2
6/4
1.4, 1.6
Gaussian Elimination; Span of a Set of Vectors
3
6/7
1.7, 2.1
Linear Dependence and Independence; Homogenous Systems, Matrix Multiplication
4
6/9
2.1, 2.3
Matrix Algebra; Invertability and Elementary Matrices
5
6/11
2.4
Inverse of a Matrix and Review
6
6/14

Midterm Exam #1
7
6/16
3.1, 3.2
Determinants; Cofactor Expansions; Properties of Determinants
8
6/18
4.1, 4.2
Subspaces; Basis and Dimension
9
6/21
4.3, 5.1
Column Space and Null Space; Eigenvalues and Eigenvectors
10
6/23
5.2, 5.3
Characteristic Polynomial; Diagonalization of a Matrix
11
6/25

Midterm Exam #2
12
6/28
6.1
Geometry of Vectors
13
6/30
6.2, 6.3
Gram-Schmidt Process; Orthogonal Projections
14
7/2
6.3, 6.4, 6.5
Least-Squares Approximation; Orthogonal & Symmetric Matrices
15
7/5

Holiday, No Class
16
7/7
5.5
Difference Equations and Review
17
7/9

Final Exam