Math 351 - Introduction to Numerical Analysis - Winter 2020

Class Information

Instructor: Tuan Pham
Section 1
Class meetings: Bexell Hall 321, MWF 9:00 - 9:50 AM

[Syllabus]   [Tentative calendar]   [Canvas site]

Office Hours

M, W, F 1:00 - 2:00 PM at Kidder Hall 268
Th 12:00 - 2:00 PM at Kidder Hall 268
W 2:00 - 3:00 PM at Kidder Hall 108 J (computer lab)

Assignments

Homework	Solution (from grader)	Worksheets
Homework 1	Solution	Worksheet 1/10
Homework 2	Solution	Worksheet 1/13, 1/17
Homework 3	Solution	Worksheet 1/20
Homework 4	Solution	Worksheet 1/27, 1/29
		Worksheet 2/5, 2/7
Homework 5	Solution	Worksheet 2/19, 2/21
Homework 6	Solution	Worksheet 2/28
Homework 7	Solution	Worksheet 3/4, 3/6
Homework 8	Solution	Worksheet 3/11

Lecture notes

Review (Mar 13): review for Final exam, link to Zoom video

Lecture 27 (Mar 11): error estimates of Riemann sums (cont.)

Lecture 26 (Mar 9): error estimates of Riemann sums

Lecture 25 (Mar 6): numerical integration, Riemann sums

Lecture 24 (Mar 4): draw quadratic spline, Matlab example

Lecture 23 (Mar 2): compute quadratic spline

Lecture 22 (Feb 28): explain Runge phenomenon; spline interpolation

Lecture 21 (Feb 26): use polynomial interpolation to approximate a function, Matlab example

Lecture 19-20 (Feb 21-24): Newton formula

Lecture 18 (Feb 19): programming Lagrange formula on Matlab, Matlab example

Lecture 17 (Feb 17): interpolation problems; Lagrange formula

Lecture 16 (Feb 14): fixed point method

Lecture 15 (Feb 12): an example of Newton's method in higher dimensions

Lecture 14 (Feb 7): bisection method and Newton's method in higher dimensions

Lecture 13 (Feb 5): stopping condition of Newton's method, Matlab example; practice on order of convergence

Lecture 12 (Feb 3): order of convergence

Lecture 11 (Jan 31): error analysis of Newton's method

Lecture 10 (Jan 29): error analysis of bisection method, Matlab example; Newton's method

Lecture 9 (Jan 27): sources of error, root-finding problem, bisection method

Lecture 8 (Jan 24): defects of arithmetics in floating-point format and consequences

Lecture 7 (Jan 22): addition and multiplication in floating-point format

Lecture 6 (Jan 17): floating-point format and fixed-point format

Lecture 5 (Jan 15): arithmetic operations in binary system

Lecture 4 (Jan 13): estimate an integral using Taylor approximation

Lecture 3 (Jan 10): error estimate of Taylor approximation, Matlab example

Lecture 2 (Jan 8): Taylor approximation

Lecture 1 (Jan 6): introduction

Remarks before / after class

Final review

Matlab practice 3

Midterm exam solution

Midterm review

Matlab practice 2

Matlab practice 1

Instructions to install Matlab

Links

Department of Mathematics
Oregon State University

This page was last modified on Monday, March 16, 2020.