MATH 3600-100 (6272), Spring 2021

Applied Numerical Methods

Syllabus

Catalog Description:
A survey of numerical methods for engineering, science and mathematics students. Topics include: solutions of systems of linear and nonlinear equations, eigenvalues, numerical differentiation and integration, and numerical solution of ordinary and partial differential equations. The topics will be posed in a setting of problems intended for engineering students using MATLAB. The course will simultaneously introduce numerical methods, programming techniques, problem solving skills and the Matlab language, in a lecture-lab format.
Desired Learning Outcomes:
Prerequisites:
MATH 3400 Elementary Differential Equations.
Class hours/ location:
None, since this class is online and asynchronous.
Web page:
http://www.ohiouniversityfaculty.com/mohlenka/2215/3600/.
Instructor:
Martin J. Mohlenkamp, mohlenka@ohio.edu.
Interaction environment:
We have a class Teams team. The main activities there are in channels:
Content questions:
If you are confused about a topic in the text or a homework problem, then ask your question here, as if you were raising your hand in class. I will answer in the channel so that others get the benefit of your question too.
Office hours:
The initial plan is to have a short scheduled office hour Monday, Tuesday, Wednesday, and Thursday afternoons. The times and frequency will then be adjusted based on usage and your input.
Social chatting:
If you want to introduce yourself, see if anybody knows of good internships, share an interesting website, post a video of your (robot) cat, etc., then do it here.
Computing Environment:
The course uses Matlab. To access it without buying your own copy, use the university's Virtual Desktop.
Text:
Introduction to Numerical Methods and Matlab Programming for Engineers, Todd Young and Martin Mohlenkamp. Available at http://www.ohiouniversityfaculty.com/youngt/IntNumMeth/.
Group component:
Group formation:
I will randomly assign groups of 3 using Blackboard. The groups will be randomly reset for each new part of the textbook, so you will be in four different groups. (By chance, you might have repeat partners.)
Partner ratings:
At the end of each part of the textbook, you will rate (and be rated by) your former partners on how much they contributed to the group. The ratings you receive are part of your grade.
Group Homework:
Each lecture in the text has a few homework problems. As a group you will submit a single solution for each problem. Submission is online through Blackboard; upload a single file (.docx or .pdf) for each problem. See the section on academic (mis)conduct below for the resources you are and are not allowed to use.
Advice: It will be tempting to just split up the problems. That works poorly because:
  1. Many problems depend on previous problems.
  2. You will learn less and suffer for it later in the course and in life.
It is best if everyone tries all the problems and then you discuss and compare. Then you can split up the task of writing a clean version of each solution and submitting it.
Individual component:
Individual homework:
One additional problem each week is done individually. Some of these will be mathematical exercises and some will help prepare you for your final project. Submission is online through Blackboard. These problems will be graded both on content and on presentation, using the Good Problems system of handouts. See the section on academic (mis)conduct below for the resources you are and are not allowed to use.
Final project:
As a culminating experience, you will do a project to apply numerical methods using Matlab to a topic outside of this course. It could be something from one of your other courses (that is not already using numerical methods), a hobby or other interest of yours, etc.
Your goal is to demonstrate what you have learned in this course and in particular to demonstrate that you have met the Desired Learning Outcomes listed at the start of this syllabus.
The deliverables for the project are:
  • A presentation, either live via video or as a recorded video (your choice). (20%; due Thursday April 19.)
  • A report. (80%; due Thursday April 26.)
Grade:
Your grade is based on group homework 50%, your partners' ratings of you 10%, your individual homework 20%, and your final project 20%. An average of 90% guarantees you at least an A-, 80% a B-, 70% a C-, and 60% a D-.
Late Work:
Group and individual homework is due at noon on the specified days. Late homework is penalized 10% per day (or part thereof) late. You can resubmit a homework to improve your score, but the late penalty will apply.
Academic (mis)conduct:
You are allowed to use most resources, but there are some limitations.
Unlimited use, without specific acknowledgment:
  • The textbook.
  • Discussions with me.
  • Your partners, for the group homework.
  • Matlab documentation.
Broad use, with acknowledgment:
  • Websites about numerical methods or Matlab.
  • Explanations by members of other groups in this class.
  • Explanations by members of your group, for the individual assignments.
  • Explanations by students who took this class in the past
Acknowledge and describe this help in writing on the problem where it was used. For example, you might write "[Name] explained to me how to do [some part] of this problem" or "I found an explanation of [concept] at the website [url]".
Forbidden:
  • The written work or programs from students who took this class in the past.
  • Websites such as Chegg that claim to have homework solutions for this class.
  • Direct copying.
A minor, first-time violation of this policy will receive a warning and discussion and clarification of the rules. Serious or second violations will result in a grade penalty on the assignment. Very serious or repeated violations will result in failure in the class and be reported to the Office of Community Standards and Student Responsibility, which may impose additional sanctions. You may appeal any sanctions through the grade appeal process.
Special Needs:
If you have specific physical, psychiatric, or learning disabilities and require accommodations, please let me know as soon as possible so that your learning needs may be appropriately met. You should also register with Student Accessibility Services to obtain written documentation and to learn about the resources they have available.
Responsible Employee Reporting Obligation:
If I learn of any instances of sexual harassment, sexual violence, and/or other forms of prohibited discrimination, I am required to report them. If you wish to share such information in confidence, then use the Office of Equity and Civil Rights Compliance.
Learning Resources:

Schedule (Subject to change)

Typical Week

Week of January 18

Monday is a Holiday. Tuesday and Wednesday you should figure out how to use all the tools and work on the lecture 1 homework with them.

Lecture 1 starts the first part of the text: Part I: Matlab and Solving Equations.

Week of January 25

Week of February 1

(From now on I will stop repeating Group homework due at noon in Blackboard: All problems from and due at noon in Blackboard. See Blackboard for the assignment..)

There is a Part I review at the end of lecture 7.

Week of February 8

Tuesday February 9 is a vacation day.

(From now on I will stop listing the days of the week unless there is some ambiguity. The due days are always available in Blackboard.)

Lecture 8 starts Part II: Linear Algebra. You will change groups.

Week of February 15

Week of February 22

Week of March 1

Lectures 17 and 18 are not used. At the end of Lecture 18 is a part II review.

Wednesday March 3 is a vacation day.

Lecture 19 starts Part III: Functions and Data. You will change groups.

Week of March 8

Week of March 15

Week of March 22

Lecture 26 is not used.

There is a Part III review at the end of lecture 28. Lecture 29 starts Part IV: Differential Equations. You will change groups.

Week of March 29

Lecture 32 is not used.

Thursday April 1 is a vacation day.

Week of April 5

Week of April 12

Lecture 40 is not used.

Week of April 19

There is a Part III review at the end of lecture 42.

Week of April 26


Martin J. Mohlenkamp

Last modified: Wed Jan 20 21:10:15 UTC 2021