Math250: Introductory Linear Algebra

Rutgers University


Instructor: Tom Benhamou

My Office: Hill 205

Office hours: Wed 11:00 am to 12:00 pm

E-Mail tom.benhamou (at) rutgers (dot) edu

Mon and Wed 05:40pm to 7:00pm at CA-A5 (CAC)

Textbook: David C Lay, Judi McDonald, and Steven R Lay, Linear Algebra and Its Application with MyLab Math 6th Edition.

Description

This course covers introductory topics in linear algebra with emphasis on matrices. The topics include Vectors in n-space, systems of linear equations, Gaussian elimination, span and linear independence of a set of vectors, matrix algebra, determinants, subspaces of n-space, basis and dimension, eigenvalues and eigenvectors, diagonalization of a matrix, the geometry of vectors, projections, orthogonal sets of vectors, symmetric matrices, and applications.

Final Grade

The final grade will be based on the results of the examinations and the solutions of the homework problems. Here are the weights of the different components of the course:
Approximated Schedule
Week Topic
1 1.1 Systems of Linear Equations, 1.2 Row Reduction and Echelon Forms, 1.3 Vector Equations
2 1.4 The Matrix Equation Ax=b, 1.5 Solution Sets of Linear Systems
3 1.7 Linear Independence, 1.8 Introduction to Linear Transformations
4 1.9 The Matrix of a Linear Transformation, 2.1 Matrix Operations, 2.2 The Inverse of a Matrix
5 2.3 Characterizations of Invertible Matrices, 3.1 Introduction to Determinants
6 3.2 Properties of Determinants, 4.1 Vector Spaces and Subspaces (introduce complex vector spaces and examples too)
7 4.2 Null Spaces, Column Spaces, and Linear Transformations, 4.3 Linearly Independent Sets; Bases
8 4.4 Coordinate Systems, 4.5 The Dimension of a Vector Space, 4.6 Change of Basis
9 5.1 Eigenvectors and Eigenvalues, 5.2 The Characteristic Equation, 5.5 Complex Eigenvalues
10 5.3 Diagonalization, 6.1 Inner Product (including Hermitian), Length, and Orthogonality, 6.2 Orthogonal Sets
11 6.3 Orthogonal Projections, 6.4 The Gram-Schmidt Process
12 6.5 Least-Squares Problems, 7.1 Diagonalization of Symmetric Matrices
13 7.2 Quadratic Forms, 7.4 The Singular Value Decomposition

Homework:

The problems are taken from the exercises sections at the end of each chapter of the textbook.

HW1: due Sep 13 11:59 pm
HW2: due Sep 20 11:59 pm
HW3: due Sep 27 11:59 pm
HW4: due Oct 11 11:59 pm
HW5: due Oct 18 11:59 pm
HW6: due Oct 25 11:59 pm
HW7: due Nov 4 11:59 pm
HW8: due Nov 15 11:59 pm
HW9: due Nov 22 11:59 pm
HW10: due Dec 2 11:59 pm Your solutions to the HW problems should be uploaded to the course Canvas page in the designated area. Please submit a clean readable scan of your solutions on time. All problems will be given from the Textbook.

Lecture notes:

In general we will follow the textbook as described in the table above. The class notes here are just to highlight the main theorems and some extra examples given in class.

Lecture notes

Further material:

Fanxin's Notes
Midterm 1-Example
Midterm 1-Fall 2024+sols
Midterm 2- Fall 2024 Preparation Questions
Midterm 2- Fall 2024 Preparation Questions-Sols
Midterm 2- Fall 2024
Midterm 2- Fall 2024 Sols
Midterm 3- Fall 2024 Preparation Questions
Midterm 3- Fall 2024 Preparation Questions-Sols