INTRODUCTION TO NUMERICAL METHODS: Analysis and Computation: MATH:3800, Section 0003
Cross-listed: CS:3700, Section 0003
Course meeting time and place: 10:30AM-11:20AM MWF, 113 MLH
Department of Mathematics
Course ICON site: To access the course site, log into Iowa Courses Online (ICON) https://icon.uiowa.edu/index.shtml using your Hawk ID and password.
Course Home: The College of Liberal Arts and Sciences (CLAS) is the home of this course, and CLAS governs the add and drop deadlines, the second-grade only option (SGO), academic misconduct policies, and other undergraduate policies and procedures. Other UI colleges may have different policies.
Description of course: Topics to be covered:
This course plan may be modified during the semester. Such modifications will be announced in advance during class periods and on the course web page; the student is responsible for keeping abreast of such changes. This is NOT a course on learning MATLAB or PYTHON! This is a mathematically oriented course on the mathematics of numerical methods (that may be used by MATLAB and PYTHON). If you are looking for a course to learn MATLAB or PYTHON then you should take for example the course ME:4111/CEE:4511 Scientific Computing & Machine Learning, it used to be called Numerical Calculations.
Learning Objectives: This course will cover some basic topics of numerical analysis at an introductory level (see the course description above for the list of topics to be covered). The main objective will be to have a clear understanding of the ideas and techniques underlying the numerical methods, results, and algorithms that will be presented, where error analysis plays an important role. You will then be able to use this knowledge to analyze the numerical methods and algorithms that you will encounter, and also to program them effectively on a computer. This knowledge will be useful in your future to solve various problems numerically.
Class procedures: The majority of each class period will be lecture oriented. It is strongly advised to read the material to be discussed before coming to class. Therefore, if there is a difficult point, you will know beforehand where it arises, so that you can benefit from the lecture more effectively. If a point remains unclear you can ask questions in class. Readings may be assigned. Standard out-of-class preparation is at least six hours per week.
Additional useful readings:
Academic Honesty and Misconduct: All students in CLAS courses are expected to abide by the CLAS Code of Academic Honesty. Undergraduate academic misconduct must be reported by instructors to CLAS according to these procedures. Graduate academic misconduct must be reported to the Graduate College according to Section F of the Graduate College Manual.
Student Collaboration on homework: The homework for this course is designed to help you master your knowledge related to the topics covered during lecture. As such, you may discuss on the homework problems with others or use online resources. However, please be aware that to master the skills needed for this class, practice is required and that to do well on the final exam you will need to work many of these problems multiple times without help. Be sure to test your knowledge by doing much of the homework on your own. Students are allowed to partially collaborate with others on homework through discussion for the most difficult problems. However, each student must turn in their own homework and it must not be a copy of someone else homework. Students are responsible for understanding this policy; if you have questions, ask for clarification. Word per word copies will not be tolerated. In extreme cases students may be requested to stop any kind of collaboration with other students.
Student Complaints: Students with a complaint about a grade or a related matter should first discuss the situation with the instructor and/or the course supervisor (if applicable), and finally with the Director or Chair of the school, department, or program offering the course. Undergraduate students should contact CLAS Undergraduate Programs for support when the matter is not resolved at the previous level. Graduate students should contact the CLAS Associate Dean for Graduate Education and Outreach and Engagement when additional support is needed.
Drop Deadline for this Course: You may drop an individual course before the deadline; after this deadline you will need collegiate approval. You can look up the drop deadline for this course here. When you drop a course, a "W" will appear on your transcript. The mark of "W" is a neutral mark that does not affect your GPA. Directions for adding or dropping a course and other registration changes can be found on the Registrar's website. Undergraduate students can find policies on dropping and withdrawing here. Graduate students should adhere to the academic deadlines and policies set by the Graduate College.
Grading System and the Use of +/-: In assigning grades, the plus/minus grading system will be used. The A+ grade will be used only in extraordinary situations. Final grades will be awarded based on the following ranges:
|100 % to 96.15 %||< 96.15 % to 88.46 %||< 88.46 % to 80.77 %||< 80.77 % to 73.08 %||< 73.08 % to 65.38 %||< 65.38 % to 57.69 %||< 57.69 % to 50.0 %||< 50.0 % to 42.31 %||< 42.31 % to 34.62 %||< 34.62 % to 26.92 %||< 26.92 % to 19.23 %||< 19.23 % to 11.54 %||< 11.54 % to 0.0 %|
Course Grades: The final grade will be based as follows:
The 2 tests and final examination are open books and open notes examinations. There will be NO question related to MATLAB or PYTHON in the tests. Smartphones/computers are not allowed. Bring a simple scientific calculator, graphing calculators are fine.
Homework: Will be assigned approximately weekly. Presentation of your results is very important. Scratch paper will not be accepted. Do not expect good grades if your solution to a problem is poorly communicated. Like for everything, if you cannot explain something in great details, you certainly have not fully understood it. The importance of doing homework cannot be overemphasized, most of human people learn by doing, not only by watching and/or listening. Late homework may not be accepted, you need to request permission first or to provide a reasonable justification. Late homework is not accepted once a correction is given. Use of symbolic mathematical software to solve problems is not allowed.
Computer languages: The predominant programming languages used in numerical analysis are Matlab and Fortran. They are available on the Linux network in MLH (see below). Alternatives to Matlab are Octave and Scilab. For programming assignments, no other language will be accepted, except Python.
Linux computer accounts: Linux computer accounts are available on the Linux network in MLH (computer lab rooms B5). To access your Linux computer account remotely. you can use FastX, a graphical Linux virtual desktop environment remotely accessible in your web browser. As long as you have an active Hawk ID and you login at least once in the past year, your CLAS Linux account will remain active. If you fail to use your account in a year, you will receive three notices, and then your CLAS Linux account will be deleted. Also, once your Hawk ID becomes inactive, your CLAS Linux account will be deleted.
Date and Time of the Final Exam: The final examination will be held on Tuesday, December 13, 2022, 5:30 PM - 7:30 PM in room W151 PPB (Pappajohn Business Building). Do not plan your end of the semester travel plans until the final exam schedule is made public. It is your responsibility to know the date, time, and place of the final exam. According to Registrar's final exam policy, students have a maximum of two weeks after the announced final exam schedule to request a change if an exam conflict exists or if a student has more than two exams in one day (see the policy here).
College of Liberal Arts and Sciences (CLAS) Course Policies:
Communication: UI Email: Students are responsible for all official correspondences sent to their UI email address (uiowa.edu) and must use this address for any communication with instructors or staff in the UI community.
Where to Get Help: Possibly the Math Tutorial Lab. More details will be given after a few weeks of classes.
Grader: Daniel Israel Kakou, office: 261 MH, mailbox is in 15 MLH (MacLean Hall), e-mail: email@example.com.