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