

JOHN CABOT UNIVERSITY
COURSE CODE: "MA 491"
COURSE NAME: "Linear Algebra"
SEMESTER & YEAR:
Fall 2020

SYLLABUS
INSTRUCTOR:
Alice Fabbri
EMAIL: [email protected]
HOURS:
MW 4:406:00 PM
TOTAL NO. OF CONTACT HOURS:
45
CREDITS:
3
PREREQUISITES:
Prerequisite: MA 198
OFFICE HOURS:
W 3:004:00 by appointment


COURSE DESCRIPTION:
This course introduces students to the techniques of linear algebra and to the concepts upon which the techniques are based. Topics include: vectors, matrix algebra, systems of linear equations, and related geometry in Euclidean spaces. Fundamentals of vector spaces, linear transformations, eigenvalues and associated eigenvectors.

SUMMARY OF COURSE CONTENT:
Linear equations and matrices; determinants and their applications; real vector spaces, with particular emphasis on inner product spaces; eigenvalues and eigenvectors.

LEARNING OUTCOMES:
Upon successful completion of the course, students will be able to:
 Solve application problems of systems of linear equations.
 Perform the operations of addition, scalar multiplication, multiplication, and find the inverses and transposes of matrices.
 Calculate determinants using row operations, column operations, and expansion down any column or across any row.
 Prove algebraic statements about vector addition, scalar multiplication, inner products, projections, norms, orthogonal vectors, linear independence, spanning sets, subspaces, bases, dimension and rank.
 Find the kernel, rank, range and nullity of a linear transformation.
 Calculate eigenvalues, eigenvectors and eigenspaces.
 Determine if a matrix is diagonalisable, and if it is, diagonalise it.

TEXTBOOK:
Book Title  Author  Publisher  ISBN number  Library Call Number  Comments  Format  Local Bookstore  Online Purchase 
Elementary Linear Algebra with applications. Ninth edition  Bernard Kolman David R. Hill  Pearson – Prentice Hal  9780132296540      

REQUIRED RESERVED READING:
RECOMMENDED RESERVED READING:

GRADING POLICY
ASSESSMENT METHODS:
Assignment  Guidelines  Weight 
Homework  Homework assignments will be graded  20% 
Mid term   30% 
Attendance  Full credit for attendance will be given to students with three or fewer unexcused absences.  10% 
Final Exam  Final exam (comprehensive)  40% 
ASSESSMENT CRITERIA:
AWork of this quality directly addresses the question or problem raised and provides a coherent argument displaying an extensive knowledge of relevant information or content. The student demonstrates complete, accurate, and critical knowledge of all the topics, and is able to solve problems autonomous BThis is highly competent level of performance and directly addresses the question or problem raised. There is a demonstration of some ability to critically evaluate theory and concepts and relate them to practice. The work does not suffer from any major errors or omissions and provides evidence that the student uses clear logic in his/her arguments. CThis is an acceptable level of performance and provides answers that are clear but limited, reflecting the information offered in the lectures. Mathematical statements are properly written most of the time. DThis level of performances demonstrates that the student lacks a coherent grasp of the material. Important information is omitted and irrelevant points included. Many mistakes are made in solving the problem raised. In effect, the student has barely done enough to persuade the instructor that s/he should not fail. FThis work fails to show any knowledge or understanding of the subjectmatter. Most of the material in the answer is irrelevant.
ATTENDANCE REQUIREMENTS:
ATTENDANCE REQUIREMENTS AND EXAMINATION POLICY
Cooperative participation in class is expected.
Full credit for attendance will be given to students with three or fewer unexcused absences. Four or more absences will result in a proportional reduction of the grade.
You cannot makeup a major exam (midterm or final) without the permission of the Dean’s Office. The Dean’s Office will grant such permission only when the absence was caused by a serious impediment, such as a documented illness, hospitalization or death in the immediate family (in which you must attend the funeral) or other situations of similar gravity. Absences due to other meaningful conflicts, such as job interviews, family celebrations, travel difficulties, student misunderstandings or personal convenience, will not be excused. Students who will be absent from a major exam must notify the Dean’s Office prior to that exam. Absences from class due to the observance of a religious holiday will normally be excused. Individual students who will have to miss class to observe a religious holiday should notify the instructor by the end of the Add/Drop period to make prior arrangements for making up any work that will be missed.


ACADEMIC HONESTY
As stated in the university catalog, any student who commits an act of academic
dishonesty will receive a failing grade on the work in which the dishonesty occurred.
In addition, acts of academic dishonesty, irrespective of the weight of the assignment,
may result in the student receiving a failing grade in the course. Instances of
academic dishonesty will be reported to the Dean of Academic Affairs. A student
who is reported twice for academic dishonesty is subject to summary dismissal from
the University. In such a case, the Academic Council will then make a recommendation
to the President, who will make the final decision.

STUDENTS WITH LEARNING OR OTHER DISABILITIES
John Cabot University does not discriminate on the basis of disability or handicap.
Students with approved accommodations must inform their professors at the beginning
of the term. Please see the website for the complete policy.


SCHEDULE



Session  Session Focus  Reading Assignment  Other Assignment  Meeting Place/Exam Dates 
Weeks 1 and 2  Linear Equations and Matrices  Chapter 1   
Weeks 3 and 4  Solving Linear Systems  Chapter 2   
Weeks 5, 6 and 7  Determinants  Chapter 3   
Weeks 8, 9 and 10  Real Vector Spaces  Chapter 4   
Weeks 10, 11 and 12  Inner Product Spaces  Chapter 5   
Weeks 12, 13 and 14  Eigenvalues and Eigenvectors  Chapter 7   
