Johannes Brust (Instr.)Khoa Tran (TA)
jjbrust@ucsd.eduk2tran@ucsd.edu
Office/student hrs:Office/student hrs:
M,W: 10a-11a (remote)T, F: 11a-12p (remote)
F: 10a-11a (APM 6422)R: 11a-1p (APM 5712)

Welcome to Math 170B (Lecture A, Winter 2022)

This page supplements materials to ``Introduction to Numerical Analysis:
Approximation and Nonlinear Equations
''

As learned in Math 170A, numerical analysis is about computational methods. As such this class involves a valuable amount of numerical reasoning in connection with practical methods. One may use the materials to further learn Numerical Analysis in Math 170C or even as tools to numerically solve problems from research, industry and applications accross a variety of different subjects.

Memo to the student:

Remember, this class is here to help succeed in learning the subject.

  • Homework problems will help prepare for Quiz, Midterm and Final questions
  • •Being active in Lecture, Discussion and office hours will help to learn
  • •Ask for help when feeling stuck

Announcements

Jan 6 • Once instruction returns to in-person learning the room is updated to APM B412
Jan 1 • Weeks 1&2 are remote (at least until Wed. Jan 17). According to campus recommendation class may transition to in-person after this period.

Syllabus

All times in Pacific Time

Lectures: MWF, 9a-9:50a in APM B412 (remote initially)

Discussions: Tu, 7p-7:50p in PCYNH 240 (remote initially)

Schedule

(Note: Schedule and policies may be updated throughout the quarter)

Remember: Remotely: Midterms, quizzes and final

Week Lect.DateTopicNotes
11Mon, Jan 03, 22Intro. & Sec. 1.1 [Lec.1]
12Wed, Jan 05, 22Secs. 1.1 & Sec. 1.2[Lec.2],[Mtlb.],[pdcst.]
13Fri, Jan 07, 22Sec. 1.2[Lec.3],[pdcst.]
24Mon, Jan 10, 22Sec. 3.1[Lec.4],[Mtlb.],[pdcst.]
25Wed, Jan 12, 22Sec. 3.1 cont.[Lec.5],[Mtlb.],[pdcst.]
26Fri, Jan 14, 22Sec. 3.2[Lec.6],[Mtlb.],[pdcst.]
37Mon, Jan 17, 22MLK Holiday
38Wed, Jan 19, 22Sec. 3.3[Lec.7],[Mtlb.],[pdcst.]
39Fri, Jan 21, 22Secs. 3.4[Lec.8],[Mtlb.],[pdcst.]
410Mon, Jan 24, 22Secs. 3.4 & 6.1 (Quiz 1)[Lec.9],[Mtlb.],[pdcst.]
411Wed, Jan 26, 22Sec. 6.1[Lec.10],[pdcst.]
412Fri, Jan 28, 22Sec. 6.2
513Mon, Jan 31, 22Sec. 6.2 cont.
514Wed, Feb 02, 22Sec. 6.3
515Fri, Feb 04, 22Midterm review
616Mon, Feb 07, 22Sec. 6.4 (Midterm)
617Wed, Feb 09, 22Sec. 6.4 cont.
618Fri, Feb 11, 22Sec. 6.5
719Mon, Feb 14, 22Secs. 6.5 & 6.6
720Wed, Feb 16, 22Sec. 6.6 cont.
721Fri, Feb 18, 22Sec. 7.1
822Mon, Feb 21, 22Presidents' Holiday
823Wed, Feb 23, 22Sec. 7.1 cont.
824Fri, Feb 25, 22Sec. 7.1 cont.
925Mon, Feb 28, 22Sec. 7.2
926Wed, Mar 02, 22Sec. 7.2 (Quiz 2)
927Fri, Mar 04, 22 TBD & review
1028Mon, Mar 07, 22TBD & review
1029Wed, Mar 09, 22TBD & review
1030Fri, Mar 11, 22TBD & review
1131Mon, Mar 14, 22TBD & review
1132Wed, Mar 16, 22Final Exam (8:00a-10:59a)

Materials

Textbook:Numerical Analysis: Mathematics of Scientific Computing (3rd ed.),
D. Kincaid and W. Cheney
Content:We will cover relevant parts of chapters 1,3,6 and 7
Homework:We will use 9 HW sets (to learn and practice the subject)
Assessment:All exams/quizzes remote via Gradescope (Pacific Times)
Quizzes available for 36 hours (spanning two days)
Quiz 1 (start: M. Jan. 24, 12pm -- end: Tu. Jan. 25, 12am),
(Content: Secs. 1.1,1.2,3.1,3.2)
Midterm (M. Feb. 7, 8pm -- 9pm),
(Content: Secs. 3.3,3.4,6.1,6.2)
Quiz 2 (start: W. Mar. 2 -- end: R. Mar. 3),
(Content: Secs. 6.3,6.4,6.5,6.6,7.1)
Final (Wed. Mar. 16, 8:00am -- 10:59am),
(Content: comprehensive)

Grading

Weighted final scores from the best of two approaches:

30% Homework + 25% Quizzes + 45% Miterm & FinalOR
30% Homework + 15% Best Quiz + 55% Miterm & Final

Letter grades from weighted final scores and the best of two options

  • (Option A):
  •  A+   A   A-   B+   B   B-   C+   C   C-   D   F 
     97   93   90   87   83   80   77   73   70   60   60> 

  • (Option B):
  • A curve where the median corresponds to B-/C+

Resources

Weblinks:

Canvas (Course page)
Gradescope (Examination system)
Piazza (Portal to ask questions)


Homework:

To access use the UCSD "AD username" (e.g., jjbrust) and "Student ID" (e.g., A1234567)

(Due/ Sections)
Homework 1, [HW1],[Soln.] (due Jan. 7, Secs. 1.1 -- 1.2)
Homework 2, [HW2],[Mtlb. Soln.],[Soln.] (due Jan. 14, Secs. 3.1 & 3.2)
Homework 3, [HW3],[Soln.] (due Jan. 21, Secs. 3.3 & partly 3.4)
Homework 4, [HW4] (due Jan. 28, Secs. 6.1 & partly 6.2)
Homework 5, (due Feb. 04, Secs. 6.2 & 6.3)
Homework 6, (due Feb. 11, Secs. 6.4 & partly 6.5)
Homework 7, (due Feb. 18, Secs. 6.5 & 6.6)
Homework 8, (due Feb. 25 Sec. 7.1)
Homework 9, (due Mar. 4, Sec. 7.2)


Instructions (homework):

• Total of 9 HW sets. Cumulative HW grade based on the best 8 out of 9.
HW 1 -- 9 submitted to Gradescope by Friday 11:00 pm Pacific Time.
(Note: To be prepared for unforeseen technical difficulties, we will accept homework submitted within 24 hours from the due date, i.e., Saturday 11:00 pm, without a penalty.)
• In view of the above arrangement, NO late homework will be accepted.
• You can work with classmates, but need to write down your own version. Copying solutions from others is not accepted and is considered cheating.
• A good portion of the exams will be based on the weekly problems. So it is extremely important for you to make sure that you understand each one of them.


Notes:

Please notice that outside factors, including the need for a certain grade for admission/retention in any academic program, scholarship or transfer credit, graduation requirements or personal desire for a specific grade DO NOT appear in the determination of course grades. Effort, improvement, class attendance and participation will all dramatically improve your grade in the course in that they will allow you to do well on exams, and the final exam. They will NOT, however, actively participate in the calculation of course grades.

Accommodations: Students requesting accommodations and services due to a disability for this course are asked to provide a current Authorization for Accommodation (AFA) letter issued by the Office for Students with Disabilities (OSD), prior to eligibility for requests. Receipt of AFAs in advance is necessary for appropriate planning for the provision of reasonable accommodations. OSD Academic Liaisons also need to receive current AFA letters. Students can find department-specific information on exam accommodations on the following Math Department webpage: http://www.math.ucsd.edu/programs/undergraduate/exam_accommodations.php

    Academic Dishonesty:  Academic dishonesty is considered a serious offense at UCSD.  Students caught cheating will face an administrative sanction which may include suspension or expulsion from the university.  It is in the student's very best interest to maintain academic integrity. (Click here for more information.)