Math 1070 Fall Semester 2017

Numerical Mathematical Analysis
MWF 10:00-10:50, 300 Old Engineering Hall

Office Hours

MWF 2:00 - 3:00, and by appointment
Office: Thackeray 606
Phone: (412) 624 5681

This course is an introduction to modern numerical methods. Topics include polynomial and spline interpolation, numerical integration and differentiation, numerical solution of nonlinear equations and ordinary differential equations. Our goal will be to understand how and when the methods work. The concept of numerical error will be used to quantify the accuracy of approximation. We will also study the stability and the efficiency of the algorithms.

Computer assignments will use Matlab, software produced by The MathWorks. The Matlab language provides extensive library of mathematical and scientific function calls entirely built-in. Matlab is available on Unix and Windows in the university computing labs. The full set of manuals is on the web in html and also in Adobe PDF format. The "Getting Started" manual is a good place to begin and is available both in html format and in Adobe PDF format. The full reference manual as well as manuals for each of the many toolboxes are all available.

Textbook: Elementary Numerical Analysis, 3rd edition by Kendall Atkinson and Weimin Han.

Course materials

  • Syllabus
  • Matlab Primer
  • Matlab Tutorial: Postscript; HTML
  • Introduction to Matlab exercises by Dr. Mike Sussman: Preliminaries; Beginning Matlab
    For useful material related to this course go to Kendall Atkinson's class web page


  • A collection of matlab codes accompanying the text
  • Some graphical user interfaces
    Additional references :
  • Numerical Mathematics, second edition, by A. Quarteroni, R. Sacco, F. Faleri. Book's Programs
  • Numerical Methods in Scientific Computing, volume I, by G. Dahlquist, A. Bjorck. SIAM.
  • Numerical Methods, by G. Dahlquist, A. Bjorck. Dover.

    Homework Assignments

  • Homework 1, Due Friday, September 8, 2017: Section 1.2 #6, 9c, 15
  • Homework 2, Due Friday, September 15, 2017: Section 2.2 #1b,d, 5b,c, 6f,h; Section 2.3 #9
  • Homework 3, Due Monday, September 25, 2017: Section 4.1 #7, 8a, 12-bonus, 23a, 25
  • Homework 4, Due Friday, October 6, 2017: Section 4.2 #1, 4; Section 4.3 #1, 11; Hermite interpolation problem
  • Homework 5, Due Friday, October 13, 2017: Section 5.1 #1, 11b,c, 16
  • Homework 6, Due Wednesday, October 25, 2017: Section 5.2 #1a, 7, 15, 19
  • Homework 7, Due Wednesday, November 1, 2017: Section 5.3 #2 - only do I-2, I-3 for 2a,b,c; #9; Section 5.4 #1a, #3 - only do a), #8, #9 - only do a)
  • Homework 8, Due Friday, November 10, 2017: Section 3.1 #1d, 9; Section 3.2 #2d, 3, 13 (extra credit); Section 3.3 #1d, 4
  • Homework 9, Due Monday, November 20, 2017: Section 3.4 #1, 5, 8, 11, 13a
  • Homework 10, Due Wednesday, November 29, 2017: Section 3.5 #1 (use the code from newton.m, error_bd = 1e-8, x0 = -1 and 1), 8
  • Homework 11, Due Wednesday, December 4, 2017

    Matlab Assignments

  • Matlab Exercise 1 (for begining matlab users). Due September 1, 2017.
  • Alternative Matlab Exercise 1 (for students familiar with matlab). Due September 1, 2017.
  • Matlab Exercise 2 (for begining matlab users). Due September 11, 2017. NOTE: this is the same as the Alternative Matlab Exercise 1.
  • Alternative Matlab Exercise 2 (for students familiar with matlab). Due September 11 2017.
  • Matlab Exercise 3. Due Wednesday October 4, 2017.
  • Matlab Exercise 4. Due October 27, 2017.
  • Matlab Exercise 5. Due November 29, 2017.


  • Exam 1: in class on Wednesday, October 11, 2017.
  • Exam 2: in class on Friday, November 10, 2017.
  • Final Exam: date to be determined by the University

    Disability Resource Services

    If you have a disability for which you are or may be requesting an accommodation, you are encouraged to contact both your instructor and Disability Resources and Services, 140 William Pitt Union, 412-648-7890 or 412-383-7355 (TTY) as early as possible in the term. DRS will verify your disability and determine reasonable accommodations for this course.

    Academic Integrity

    Cheating/plagiarism will not be tolerated. Students suspected of violating the University of Pittsburgh Policy on Academic Integrity will incur a minimum sanction of a zero score for the quiz, exam or paper in question. Additional sanctions may be imposed, depending on the severity of the infraction. On homework, you may work with other students or use library resources, but each student must write up his or her solutions independently. Copying solutions from other students will be considered cheating, and handled accordingly.

    Statement on Classroom Recording

    To address the issue of students recording a lecture or class session, the University’s Senate Educational Policy Committee issued the recommended statement on May 4, 2010. “To ensure the free and open discussion of ideas, students may not record classroom lectures, discussion and/or activities without the advance written permission of the instructor, and any such recording properly approved in advance can be used solely for the student’s own private use.”