Professor: | Dr. Anne Shepler |
Office: | GAB 471B, phone: 940-565-4943 |
Office hours: | Mon 10--12, Wed 10--12; by appt |
Web: | http://www.math.unt.edu/~ashepler/Math2700F17.html |
Prerequisites: | Math 1720 or math department placement |
Text: | Linear Algebra and Its Applications, Edition 5, by Lay, Lay, and McDonald |
Calculator: |
TI-83 |
Course
Description: The course covers linear
equations in linear
algebra, matrix algebra, determinants, vector spaces, span, independence,
rank, dimension, eigenvalues
and eigenvectors, and orthogonality.
Grading: Course grade is based on
Date/Time of Final: The Final Exam will be in our regular classroom Wh 116.
Calculator: If an exam allows calculator use, TI 83, TI 83 Plus, TI 84, TI 84 Plus may be used. TI 89’s, TI 92’2, Nspires, or any other utility with alphanumeric capabilities ARE NOT permitted. Calculators may not be shared during exams.
Homework:
Come to lecture each Friday with your homework stapled and ready to turn in at the
beginning of class. Your lowest 2 homework scores will be
dropped automatically to cover homework missed due to
illness, family emergency, transportation problems, oversleeping, injury, work
schedule, completing the wrong section, completing the wrong problems,
tornados, eclipses, etc.
Homework that is difficult to read will earn a zero score. Only
hardcopy written work will be accepted, no faxes or emails or scans
will be accepted. (ODA students may have exceptions.)
Written work: Show all your work (in clear steps) on exams and homework. No (or little) work shown usually earns no credit---even if the answer is correct. Solutions must be clear, concise, complete, and correct. Your audience should be an average student in this course, someone who has read the problem but does not know a solution. Your solution must contain more detail than the solution guide in the back of the book. In general, solutions without enough detail or with confused steps will earn little or no credit.
Expectations:
You are expected to come to every lecture and come on time.
Plan ahead so you are not late. You are responsible for everything
that happens in class. You are
expected to read the assigned sections and work on the homework
problems
immediately after they are assigned. You should be prepared to ask
questions,
take notes, and look alive in class. Leave all electronic gadgets
turned off and out of reach. Feel
free to bring beverages to class (coffee, cola, tea, water, etc.) or
quiet snacks to help you participate. It is the student's
responsibility to obtain notes from another student if class is missed.
Disabilities: It is the responsibility of students with certified disabilities to provide the instructor with appropriate documentation from the Dean of Students Office before Sept. 15th.
Extra Credit: Do not expect to be able to do some extra work to help your grade either before or after the final exam. There will be no extra credit during the semester, except possibly an extra problem on an exam. You must complete the assigned work on time.
Cheating:
Academic honesty is a minimal expectation for this and all UNT
classes. Anyone caught cheating will receive an F for the
course. Furthermore, a letter will be sent to the appropriate
dean who may take further disciplinary action.
Any
gadget out (except an approved calculator) during an exam will be
interpreted as academic dishonesty. (Keep your electronic gizmos
zipped in a backback.)
Email: Instructors sometime receive 50-100 academic emails a day, and UNT sometimes moves faculty emails. Help your emails get prompt attention. Put all your information into ONE email and keep the email BRIEF. Write in complete sentences with appropriate grammar. Your subject line should include 4 things: course name, time the course meets, your full name, and a subject word, for example," SUBJECT: Math 2700 at 11am, Jane Doe, brain surgery". Save your math questions for in person; I do not explain math over email because the limitions in notation often cause confusion.
Learning Outcomes: Students will devlop skills in solving problems involving linear relations, learn to solve linear systems using matrix algebra, recognize linear systems as linear transformations, solve for determinants and interpret information provided by determinants, learn tools of working in vector spaces, compute eigenvalues and eigenvectors.
Rough Schedule
(subject to change): Weeks 1--4: systems of linear
equations, row reduction and echelon forms, vector equations, matrix
equation, solution sets of linear systems, linear independence, linear
transformations; Weeks 5--6: matrix operations, inverse of a matrix,
characterizations of invertible matrices; Weeks: 7--9: introduction to
determinants, properties of determinants, cramer’s rule; Weeks
9--11: vector spaces and subspaces, null & column spaces, linear
transformations, linear independent sets, bases, dimension of a vector
space, rank; Weeks 12-14: eigenvectors and eigenvalues,
characteristic equation, diagonalization; Time Permitting: inner product, length, and orthogonality
Math 2700: Linear Algebra
Homework Problems
Section |
Problems |
Due |
"How Google Finds Your Needle in the Web's Haystack" |
Handout |
|
1.1 Systems of linear equations |
1--22, 33, 34 |
|
1.2 Row
reduction and
echelon forms |
4, 10, 12, 20, 23, 24 |
|
1.3 Vector
equations |
5--21, 25--27 |
|
1.4 The
matrix equation
Ax=b |
1--20 |
|
1.5 Solution
sets of
linear systems |
1--22 |
|
1.7 Linear
independence |
1--14, 27, 28, 30 |
|
1.8 Linear
transformations |
1--17 |
|
2.1 Matrix
operations |
1-11 |
|
2.2 The
inverse of a
matrix |
1--8, 13--18, 29--33 |
|
2.3 Characterizations
of
invertible
matrices |
1--10 (Use Calculator) , 13--17 |
|
3.1 Introduction
to
determinants |
1--30 |
|
3.2 Properties
of
determinants |
1--20 |
|
3.3 Cramer’s
rule |
1--16 |
|
4.1 Vector
spaces and
subspaces |
1--18 |
|
4.2 Null
& column
spaces |
1--24 |
|
4.3 Linear
independent
sets, bases |
1--16 |
|
4.5 The
dimension of a
vector space |
1--18 |
|
4.6 Rank |
1--16 |
|
5.1 Eigenvectors
and eigenvalues |
1--20 |
|
5.2 The
characteristic
equation |
1--20 |
|
5.3 Diagonalization |
1--20 |
|
6.1 Inner
product,
length, and orthogonality |
TBA |
|
6.2 Orthogonal
sets |
TBA |
|
6.3 Orthogonal
projections |
TBA |