University of Minnesota
CSci 5302 - Analysis of Numerical Algorithms

CSci 5302 -- Spring 2018 -- Course Syllabus

Analysis of Numerical Algorithms

Preliminary: Subject to changes and corrections

Class Hours
Lecture: Tuesday Thursday 4:00-5:15pm in Keller 3-111

Scientific Computing: An Introductory Survey; by Michael T. Heath (2nd edition) McGraw Hill, 2002

Instructor: Prof. Daniel Boley,
Office: Keller bldg, room 6-209
Phone: 612-625-3887
Office Hours: TTh 9:30-10:15 + Tuesday right after class.
To avoid my e-mail spam filter, please include the string "5302" in the subject line.

TA: Tatiana Lenskaya
Office: Keller bldg, room 2-209 (during office hour)
Phone: 612-626-7512 (during office hour)
Office Hours: Wed 3-4pm or by appt.

Assignment Plan (not in order)

  • Several classroom exercises and/or pop quizzes: up to 10% of final grade
  • 3 midterms: 60% of final grade
  • 4-6 assignments: 30% of final grade
  If the number of exams and/or assignments changes, the relative weights will be adjusted.

General Information
This course introduces the basic numerical techniques to solve mathematical problems on a digital computer. Algorithms for several common problems encountered in mathematics, science and engineering are introduced. The pitfalls and errors that can arise when solving mathematical problems with methods taking finite time and in finite precision arithmetic are discussed, and measures to predict when such pitfalls are encountered will be introduced.


  • Scientific Computing - Goals and Fundamentals (Chap 1)
  • Linear Equations (a review - Chap 2, secs 1-4)
  • Nonlinear Equations (Chap 5)
  • Polynomial Interpolation, Splines (Chap 7)
  • Linear Least Squares (Chap 3)
  • Optimization Problems (Chap 6)
  • Numerical Integration and Quadrature (Chap 8, secs 1-6)
  • Initial Val. Probs. for Ord. Diff. Equs (Chap 9)

    ... time and interest permitting ....

  • Fast Fourier Transform (Chap 12)
  • Boundary Val. Probs. for Ord. Diff. Equs (Chap 10)
  • Matrix eigenvalues and singular values (Chap 4, secs 1, 2, 3, 5)
  • Random Number Generation (Chap 13)

Students will be expected to implement several of the algorithms on a digital computer in MATLAB. In the cases where another equivalent interactive programming environment is allowed, you will be responsible for implementing the equivalent features and may find only limited help from the instructional staff. Students should be familiar with basic programming techniques, as well as being able use the help system in MATLAB. Students should also be acquainted with the basic concepts of the more elementary mathematical and numerical methods (e.g. solving simple linear equations, root-finding, computing averages, using derivatives to find the minimum of a scalar function, etc.) though some of this will be reviewed during the course.

All items handed in to be graded must represent the individual effort of whoever's name(s) appears on the item. At a minimum, violators of this policy may fail the course and/or may have their names recorded at appropriate University or Departmental offices. Mutual discussion of each individual's results in the homeworks is encouraged, as long as the results themselves represent individual efforts. If you use or submit any material or software you obtained from the WWW or any other source outside of class, you must cite it. In some assignments, you may be restricted on what software you can use.

Some assignments may be assigned to be done by pairs of students; such items should be handed in as a single item listing the names of all participants. To pass the course, you will have to achieve a passing grade on the exams alone, and do satisfactorily on the homeworks. Any questions about the grading of any item must be asked within a week of when items are first handed back to students. After one week has passed, the scores become final.

Unless otherwise stated, homeworks may be submitted electronically through canvas. We are not responsible if we cannot read your handwriting, or if electronic scans of written material are unreadable. Even if late, all submissions should be submitted as a single unit directly to canvas or to the instructor or TA (no parts submitted separately at a later time). Anything submitted electronically must as a single file in PDF or plain text (no Word files), except in cases in which we ask for your code to be submitted separately. When more than one file must be submitted, use 'zip' to pack all the files into a single archive (do not use 'rar', 'tar', '7zip' or any other archiver). We are not responsible if we have any problems reading it.

Late submissions: Homeworks will be accepted until answers have been posted and up to two working days after the due date (whichever occurs first) with a deduction of 5% of the total grade per day or fraction. Answers could be posted any time after the class time on the due date without advance notice. Classroom exercises handed in outside of class will be accepted only up to the following morning. Exercises handed in outside of class by the following morning receive only half credit (except for UNITE students). The exercise questions are posted online right after class, so even if you miss class you may hand in an exercise answer sheet electronically. UNITE students should scan and e-mail their classroom exercises the same day, or fax them by the following morning. You can miss up to one classroom exercise during the semester with no penalty. These deadlines may be extended for excused absences on a case-by-case basis.

Back to class home page.