Help
This course has an assignment that is due by 11:55 pm Central Standard Time on Wednesday night of the first week of class.  Failure to complete this assignment will result in your removal from the course for non-participation. 

Textbooks

Linear Algebra with Applications (2nd ed.) by Jeffery Holt, published by W.H. Freeman

Online access to the courseware is the only resource required for this course. The math homework will be done in the WebAssign Courseware (online). You must purchase the online access. The recommendation is that you purchase it directly from Cengage Learning. However, if you need to use a CMU book voucher, then it is also available through MBS Bookstore. If you would like a physical textbook to read, the option below shows the bundle you will need to purchase to receive that.

Product

13 Digit ISBN

Courseware Required + eBook*

978-1-4641-9370-5

Courseware + eBook* + Loose-Leaf Textbook (optional)

978-1-319-13382-5

* Included eBook can only be accessed online through the courseware.

There is a two week free access so you should be able to have Online access the first day of the course.

On the day the course opens, the instructor will provide you with a Course Key. You can use the Course Key and purchase directly from the publisher on that day at this address: https://www.webassign.net/wa-auth/class-key/enroll

Course Description

3 hours. Introduction to matrix algebra and vector fields, with applications. Prerequisite: MA118 or MA112

Course Objectives

Upon successful completion of this class, students will be able to:

  • Use matrices to solve linear systems and interpret inconsistent systems
  • Use determinants to solve linear systems
  • Interpret quantities of vectors like the norm, dot product and cross product geometrically
  • Verify the properties of a real vector space for given examples
  • Determine if a set of vectors is linearly independent
  • Find the dimension of a vector space and construct a basis
  • Analyze the relationship between row space, column space and null space for a coefficient matrix of a linear system
  • Compute lengths, distances and angles using the Euclidean inner product
  • Compute eigenvalues and eigenvectors of linear transformations
  • Compute the kernel, rank and nullity of linear transformations