Math 235 - Introduction to Linear Algebra
Fall 2022
This is the Course Website with specific information for Math 235 Section 3. Information regarding all sections can be found here. We will use Moodle to post some course material and to record grades.
We meet: MW 2:30 - 3:45 pm in Goessmann Lab Room 51
The syllabus is here. It contains the information in this website and a little more.
Most Important Rule:
Ask questions! There are no silly questions!
I endorse Federico Ardila's axioms.
Axiom 1. Mathematical talent is distributed equally among different groups, irrespective of geographic, demographic, and economic boundaries.
Axiom 2. Everyone can have joyful, meaningful, and empowering mathematical experiences.
Axiom 3. Mathematics is a powerful, malleable tool that can be shaped and used differently by various communities to serve their needs.
Axiom 4. Every student deserves to be treated with dignity and respect.
Office Hours and Contact Information
Instructor: Cristian Rodriguez
Email: rodriguez@math.umass.edu
Office: LGRT 1341
Office Hours:
Fridays 9:30 - 10:30 am
Wednesdays 1:15 - 2:15 pm
By Appointment.
Piazza
We shifted to Discord!
Required Course Material
Textbook: Linear Algebra and Its Applications (6th edition) by David Lay, Steven Lay, and Judi McDonald.
Online Homework System: We will use the online homework system MyMathLab. An electronic copy of the textbook is also included in your purchase of MyMathLab. I will provide a handout with details to register in the course in MyMathLab. Use your @umass.edu email when enrolling.
Course Outline
We will roughly cover chapters 1 to 6 of our textbook. You can find the tentative schedule and our class log here.
Chapter 1 - Linear Equations in Linear Algebra:
Systems of linear equations (1.1), Row reduction and echelon forms (1.2), Vector equations (1.3), The matrix equation Ax = b (1.4), Solutions sets of linear systems (1.5), Linear independence (1.7), Introduction to linear transformations (1.8), The matrix of a linear transformation (1.9).
Chapter 2 - Matrix Algebra:
Matrix Operations (2.1); The Inverse of a Matrix (2.2); Characterizations of Invertible Matrices (2.3).
Chapter 3 - Determinants:
Introduction to determinant (3.1); Properties of Determinants (3.2); Cramer’s Rule, Volume and Linear transformations (3.3).
Chapter 4 - Vector Spaces:
Vector Spaces and Subspaces (4.1); Null Spaces, Column Spaces, and Linear Transformations (4.2); Linearly Independent Sets; Basis (4.3); Coordinate Systems (4.4); The Dimension of a Vector Space (4.4), Rank (4.6); Change of Basis (4.7).
Chapter 5 - Eigenvalues and Eigenvectors:
Eigenvectors and Eigenvalues (5.1); The Characteristic Equation (5.2); Diagonalization (5.3); Eigen- vectors and Linear Transformations (5.4); Complex Eigenvalues (5.5).
Chapter 6 - Orthogonality and Least Squares
Inner Product, Length, and Orthogonality (6.1); Orthogonal Sets (6.2); Orthogonal Projections (6.3); The Gram-Schmidt Process (6.4); Least-Squares Problems (6.5 - if time permits).
Important Dates
First day of class .................................... Tuesday, September 6
Last day to add/drop ............................. Monday, September 12
Indigenous People Day (No Class) ..... Monday, October 10
Midterm I ................................................ Monday, October 17
Last day to drop with W ......................... Tuesday, November 1
Midterm II ............................................... Monday, November 21
Thanksgiving Break ............................... Wednesday, November 23
Last day of Classes ............................... Monday, December 12
Final Exam .............................................. TBD
Grading Policy
The grade will be computed as follows:
MyMathLab Homework (15%)
Quizzes (15%)
Class Participation (5%)
Exams (65%): For more information regarding exams you can go here.
Midterm I (20%): 7-9pm on Monday October 17.
Midterm II (20%): 7-9pm on Monday, October 21.
Final Exam (25%): TBD
For information about Homework and Quizzes go here.
Grading Scale
The course letter-grade scale is:
There is no rounding of grades; for example, a 89.999999 is an A- and not an A. To receive a passing grade you have to get at least 35% in each exam.
Accommodation Policy Statement
UMass Amherst is committed to providing an equal educational oppor- tunity for all students. A student with a documented physical, psychological, or learning disability on file with Disability Services may be eligible for academic accommodations to help them succeed in this course. If you have a documented disability that requires an accommodation, please notify your instructor during the first two weeks of the semester so that we can make appropriate arrangements. Information on services and materials for registering with Disability Services are also available on their website.
Academic Honesty
We will follow the UMass Code of Conduct. See this link.