Math 351 - Introduction to Numerical Analysis - Fall 2019

Class Information

Instructor: Tuan Pham
Grader: Michael Kupperman
Section 1
Class meetings: Strand Agriculture Hall 210, MWF 3:00 - 3:50 PM
[Syllabus]   [Tentative calendar]   [Canvas site]

Office Hours

MWF 1:00 - 1:50 PM at Kidder Hall 268
MF 4:00 - 5:00 PM at Kidder Hall 268
W 4:00 - 5:00 PM at Kidder Hall 108 J (computer lab)

Assignments

Homework Solution (from grader) Worksheets
Homework 1 Solution Worksheet 9/30, 10/4
Homework 2 Solution Worksheet 10/7, 10/9
Homework 3 Solution Worksheet 10/14, 10/18
Homework 4 Solution Worksheet 10/23, 10/25
Midterm review Solution Worksheet 10/28, 10/30
Homework 5 Solution Worksheet 11/06
Homework 6 Solution Worksheet 11/13
Homework 7 Solution Worksheet 11/20
Homework 8 Solution Worksheet 11/22, 11/27
Optional assignment Worksheet 12/06
Final review

Lecture notes

  • Lecture 26 (Dec. 4): Simpson's rule
  • Lecture 25 (Dec. 2): theoretical and empirical rate of convergence
  • Lecture 24 (Nov. 27): practice on error estimates of left-point, right-point, midpoint, trapezoid methods, Example
  • Lecture 23 (Nov. 22+25): error estimates of left-point, right-point, midpoint methods
  • Lecture 22 (Nov. 20): introduction to numerical integration
  • Lecture 21 (Nov. 18): error estimates, Runge phenomenon, Example
  • Lecture 20 (Nov. 15): error estimates of polynomial interpolation, Example
  • Lecture 19 (Nov. 13): practice with Newton formula, Example
  • Lecture 18 (Nov. 8): programming Lagrange formula; Newton formula, Example
  • Lecture 17 (Nov. 6): Lagrange polynomial interpolation
  • Lecture 16 (Nov. 4): interpolation problems
  • Lecture 15 (Oct. 28): fixed point method
  • Lecture 14 (Oct. 25): efficiency of a numerical method; secant (chord) method
  • Lecture 13 (Oct. 23): order of convergence
  • Lecture 12 (Oct. 21): error estimate of Newton's method
  • Lecture 11 (Oct. 18): Newton's method, issue with 'a priori' error estimate
  • Lecture 10 (Oct. 16): bisection method for multivariable functions, Newton's method
  • Lecture 9 (Oct. 14): bisection method—error estimate, Example
  • Lecture 8 (Oct. 11): bisection method, Example
  • Lecture 7 (Oct. 9): consequences of floating-point arithmetic
  • Lecture 6 (Oct. 7): rounding and multiplication of floating-point numbers
  • Lecture 5 (Oct. 4): practice on floating-point numbers
  • Lecture 4 (Oct. 2): double precision floating-point numbers
  • Lecture 3 (Sep. 30): practice on Taylor approximation, Example
  • Lecture 2 (Sep. 27): approximation by Taylor polynomials
  • Lecture 1 (Sep. 25): introduction, Example

    • Remarks before / after class

  • Matlab Practice 3
  • Solution to midterm exam
  • Some of you pointed out the Matlab doesn't graph the function x^(1/3) properly on the negative side when you write x.^(1/3). You can fix this by using the 'nthroot' command: nthroot(x,3) where x is an array.
  • Matlab Practice 2
  • Bring a calculator to class meeting on Monday Oct 14.
  • Matlab Practice 1
  • Instructions to install Matlab

    • Links

    Department of Mathematics
    Oregon State University
    This page was last modified on Tuesday, December 10, 2019.