Fall 2022 - MATH 232 D400

Applied Linear Algebra (3)

Class Number: 4151

Delivery Method: In Person

Overview

  • Course Times + Location:

    Mo, We, Fr 1:30 PM – 2:20 PM
    SRYC 2600, Surrey

  • Prerequisites:

    MATH 150 or 151 or MACM 101, with a minimum grade of C-; or MATH 154 or 157, both with a grade of at least B.

Description

CALENDAR DESCRIPTION:

Linear equations, matrices, determinants. Introduction to vector spaces and linear transformations and bases. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. An emphasis on applications involving matrix and vector calculations. Students with credit for MATH 240 may not take this course for further credit. Quantitative.

COURSE DETAILS:

Topics Outline:  Linear equations, matrices, determinants. Introduction to vector spaces and linear transformations and bases. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. An emphasis on applications involving matrix and vector calculations.


Topic Details:

Vectors
  • Vectors in Euclidean n-Space
  • Dot Product and Orthogonality
  • Lines and Planes
Systems of Linear Equations
  • Row Reduction (Gaussian elimination) to Echelon form
  • The Geometry of Linear Systems
  • Applications in business, science and engineering
Matrices
  • Matrix operations
  • Matrix inverse; and properties of matrices
  • Elementary matrices and calculating matrix inverses
  • Matrices with special forms.
Linear Transformations
  • Matrices as transformations
  • Geometry of Linear Transformations
  • Kernel and range
  • Composition and Invertibility
  • Application to Computer Graphics (optional)
Determinants
  • Calculating determinants
  • Properties of determinants
  • Cramer's rule (optional)
Complex Numbers
  • Arithmetic in Cartesian co-ordinates.
  • The complex plane, complex conjugate, magnitude and argument (phase).
  • Polar form, De Moivre's formula and Euler's formula.
  • Roots of quadratic polynomials.
Eigenvalues and Eigenvectors
  • Properties and geometry
  • Complex eigenvalues and complex eigenvectors
  • Dynamical Systems and Markov Chains
  • Application to Economics: the Leontief model (optional)
  • The Power Method; Application to Internet Search Engines
  • Matrix Similarity and Diagonalization
Subspaces of R^n
  • Subspaces and Linear Independence
  • Basis and Dimension
  • The Fundamental Spaces of a Matrix
  • Rank
  • Change of basis
Orthogonality
  • Projection
  • Orthogonal bases and the Gram Schmidt process
  • Orthogonal matrices (optional)
  • Application to least squares approximation

Course Delivery

  •  Midterm(s): synchronous; date: TBA
  •  Final exam: synchronous; date: TBA

Grading

  • Quizzes (5, every other week, 15 min in length, not during midterm weeks) 15%
  • Computing Assignments (5, every other week, not during midterm weeks) 15%
  • Midterms (2, 15% each) 30%
  • Final Exam 40%

NOTES:

THE INSTRUCTOR RESERVES THE RIGHT TO CHANGE ANY OF THE ABOVE INFORMATION.
Students should be aware that they have certain rights to confidentiality concerning the return of course papers and the posting of marks.
Please pay careful attention to the options discussed in class at the beginning of the semester.

REQUIREMENTS:

This course is delivered in person, on campus. Should public health guidelines recommend limits on in person gatherings, this course may include virtual meetings. As such, all students are recommended to have access to strong and reliable internet, the ability to scan documents (a phone app is acceptable) and access to a webcam and microphone (embedded in a computer is sufficient). 

Materials

REQUIRED READING:

An Introduction to Linear Algebra
Daniel Norman and Dan Wolczuk
3rd Edition
Pearson

The SFU Bookstore will stock both the hardcopy and the electronic version of this textbook. Students are encouraged to obtain the hardcopy.
ISBN: 987-0-13-468263-1

RECOMMENDED READING:

Supplemental book (downloaded as a free .pdf):
 
Introduction to Applied Linear Algebra Vectors, Matrices, and Least Squares
Stephen Boyd and Lieven Vandenberghe

ISBN: 978-1-316-51896-0

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html