# Introduction to Linear and Matrix Algebra

Edfinity is supported by the National Science Foundation

## Info

This is an online homework companion to Introduction to Linear and Matrix Algebra. It comprises hundreds of algorithmic problems carefully organized into problem sets mapped to textbook sections. Use this course as-is, or customize at any level. You can mix-and-match problems from other catalog courses, add problems from the Edfinity problem repository, or write your own.

How to use this course

1. Homework: Assign high quality problems with hints and personalized feedback to develop problem-solving skills.
2. Testing: Create summative secure online quizzes and tests in minutes.
3. Supplementary resources: Embed videos, class notes, and applets alongside assignments.
4. Intervention: Use rich analytics to identify and monitor at-risk students for timely intervention.
5. Analytics: Drill down into student performance and identify problematic or difficult topics.
6. Flipped classroom: Assign pre-class assignments. Save precious class time for discussions.
7. Emporium classes: Use Edfinity for individual/group work for large enrollment sections in labs.
Interactive, algorithmic problems
Algebraic, graphing, open response; randomized variants, hints, and tips
to fill learning gaps.
Corequisite course structures
Use pre-built corequisite content,
LMS integration and accessibility
Connect to your LMS in minutes. VPAT here.
WeBWorK-compatible
Import and author WeBWorK problems.

## Syllabus

1. Edfinity Demo
2. 1 1 Vectors And Vector Operations
3. 1 2 Lengths, Angles, And The Dot Product
4. 1 3 Matrices And Matrix Operations
5. 1 4 Linear Transformations
6. 1 A Areas, Volumes, And The Cross Product
7. 1 B Paths In Graphs
8. 2 1 Systems Of Linear Equations
9. 2 2 Elementary Matrices And Matrix Inverses
10. 2 3 Subspaces, Spans, And Linear Independence
11. 2 4 Bases And Rank
12. 2 A Linear Algebra Over Finite Fields
13. 2 B Linear Programming
14. 2 C More About The Rank
15. 2 D The Lu Decomposition
16. 3 1 Coordinate Systems
17. 3 2 Determinants
18. 3 3 Eigenvalues And Eigenvectors
19. 3 4 Diagonalization
20. 3 A More About Determinants
21. 3 B Power Iteration
22. 3 C Complex Eigenvalues Of Real Matrices
23. 3 D Linear Recurrence Relations