MTH201S22019/20 – LINEAR ALGEBRA II
Email: [email protected]
Web: www.fuotuoke.edu.ng/
Class Hours: 2hrs
Virtual Classroom: hostclass.courses
Office: Faculty of Science, Mathematics Departmental block, room 4.
Office Hour: Thursdays 3pm4pm
Instructor: EGBUHUZOR Udechukwu P.
Course Description:
MTH 201 – LINEAR ALGEBRA II (2 CREDIT UNITS)
Prerequisite – MTH102
Vector Spaces: Review of basic definitions and examples of vectors and vector spaces. Topics include subspaces, linear dependence and independence of vectors, basis and dimension of a vector space, Homomorphism and quotient space, direct sum of vector spaces, and dual spaces.
Linear Mappings and Matrices: Topics include linear mappings, general linear transformation of ndimensional into mdimensional space, matrix representation of a linear map, similar matrices and change of basis, eigenvalue and eigenvectors. Others are characteristic polynomial and characteristic equation, CaleyHamilton theorem and orthogonal diagonalisation.
Canonical Forms: Primary decomposition theorem, Triangular Jordan and Rational forms for linear operator (square matrices), quadratic and bilinear forms.
Resources:
 Textbook Title
Linear Algebra with Applications, 3rd Edition, Author Otto Bretscher; Publisher Prentice Hall. Copyright 2000 ISBN139780131453340
Weblink:http://vig.prenhall.com/catalog/academic/product/0,1144,0131453343TOC,00.html  Linear Algebra, S. Lipchitz (Schaum’s Outline Series) Mc GrawHill (1987)
Homework
Look through the texts and try your hands on some of the exercises. Engage in solving the numerous exercises and kindly submit your work on or before the required time.
Assignments and Examination
There will be two assignments and one virtual examination at the end of the semester. The final exam will be cumulative. Assignments would be submitted electronically and within the stipulated time. Extension will not be accepted except on some special consideration duly given by Egbuhuzor Udechukwu
Grading Policy
The following grading scale will be used:
 5% of your score shall be based on your virtual classroom attendance
 10% shall be based on homework
 15% shall be based on assignment and participation
 70% shall be based on examination
The final grade would be based on your total grade percentage.
Course Policies
Participation
I expect you to participate in all class activities as listed on the course calendar. Participation includes, but is not limited to, the following:
 Completing all class assignments on time
 Actively engaging in class discussions
 Asking thoughtful questions during zoom class
 Proactively seeking guidance from the instructor when needed
Attendance Policy
Attendance is expected in all virtual classes. Valid excuses for absence will be accepted before class. In extenuating circumstances, valid excuses with proof will be accepted after class. Late submissions of homework will be granted for no penalty if a valid excuse is communicated to the instructor before the due date. After the due date, late submission will be granted for a 50% deduction to the score up to 2 days. After this no late submission will be granted.
Schedule and Weekly Learning Goals
The schedule is tentative and subject to change. The learning goals below should be viewed as the key concepts you should grasp after each week, and also as a study guide before each exam, and at the end of the semester. Each exam will test on the material that was taught up until the week of the exam. The applications in the second half of the semester tend to build on the concepts in the ﬁrst half of the semester though, so it is still important to at least review those concepts throughout the semester.
Week 01: Vector Spaces
 Lecture 1: Review of basic definitions and examples of vectors and vector spaces.
Week 02:
 Lecture 2: Topics include subspaces, linear dependence and independence of vectors
Week 03:
 Lecture 1: basis and dimension of a vector space, Homomorphism and quotient space
Week 04:
 Lecture 1: direct sum of vector spaces, and dual spaces.
Week 05: Linear Mappings and Matrices
 Lecture 1: Topics include linear mappings.
Week 06:
 Lecture 1: general linear transformation of ndimensional into mdimensional space, matrix representation of a linear map,
Week 07:
 Lecture 1: similar matrices and change of basis, eigenvalue and eigenvectors
Week 08: Descriptive Statistics
 Lecture 1: eigenvalue and eigenvectors. Others are characteristic polynomial and characteristic equation
Week 09:
 Lecture 1: CaleyHamilton theorem and orthogonal diagonalisation.
Week 10: Canonical Forms
 Lecture 1: Primary decomposition theorem, Triangular Jordan and Rational forms for linear operator (square matrices), quadratic and bilinear forms.
Revision
Week 11: Examination
Course Features
 Lectures 10
 Quizzes 0
 Duration 50 hours
 Skill level 200 levels
 Language English
 Students 9
 Assessments Yes

View Course Contents (Lecture Notes and Videos)