Scientific Computing with Matlab (Math 365)
In this course, we will learn how to use Matlab to solve problems in science and engineering using computational methods. We learn basic numerical methods, including solving linear systems, interpolation, quadrature rules, and solving ordinary differential equations. We also learn about visualizing output using Matlab graphing tools, programming concepts, and how to develop numerically efficient codes. This course does not assume any prior programming knowledge, although if you don't have any programming experience, you will find this course to be challenging initially.
 Basic course information
 Recommended and suggested textbooks
 Lectures
 Homework assignments
 Matlab Tutorials
 Final Project
 Grading policy
Send me an email
Please send me an email at donnacalhoun@boisestate.edu so that I can compile an email list for the class. At the very least, include a subject header that says "Math 365". You may leave the message area blank, if you wish, or send me a short note about what you hope to get out of this course.
Basic course information
Instructor  Prof. Donna Calhoun 
Time  Tues/Thurs 12:001:30 
Place  MG136 (Math Computing Lab) 
Office Hours  Thursday 1:152:45 
Prerequesites  Math 333 or Math 301 
Recommended and suggested textbooks
 Numerical Computing with Matlab, by Cleve Moler. Mathworks, Inc., (2004) (required).
 Matlab software (free for BSU Students), by Mathworks, Inc.. (required).
 Matlab software (for purchase from Mathworks, Inc.), by Mathworks, Inc.. (required  but same as above).
 Learning Matlab, by Toby A. Driscoll. The Society for Industrial and Applied Mathematics, (2009) (suggested).
Lectures
Below are the slides from lecture material that I can make available online.
Week #1 (Aug. 21) 
Tuesday 
Introduction to Scientific Computing; Arithmetic expressions
Thursday 
Assigning Variables

Week #2 (Aug. 28) 
Tues 
Graphing; working with arrays

Week #3 (Sep. 4) 
Tuesday 
1d Arrays  continued
Thursday 
More on arrays

Week #4 (Sep. 11) 
Tuesday 
Root finding  Bisection
Thursday 
No class!

Week #5 (Sep. 18) 
Tuesday 
Root finding  Fixed point, Newton's method
Thursday 
Rootfinding; Minimization

Week #6 (Sep. 25)  
Week #7 (Oct. 2 ) 
Tuesday 
Gaussian Elimination
Thursday 
Quiz #1 : Circuit problem

Week #8 (Oct. 9) 
Tuesday 
Gaussian Elimination for sparse systems

Week #9 (Oct. 16) 
Tuesday 
Timing Gaussian Elimination
Thursday 
Operation counts; logspace;

Week #10 (Oct. 23) 
Tuesday 
Using graphics handles
Thursday 
Linear regression; curve fitting

Week #11 (Oct. 30)  
Week #12 (Nov. 6) 
Tuesday 
Lagrange polynomials (cont.)
Thursday 
Barycentric Formula

Week #13 (Nov. 13) 
Tuesday 
Piecewise polynomial interpolation
Thursday 
Quiz #3 : Polynomial interpolation

Week #14 (Nov. 27) 
Thursday 
Quadrature rules; Solving ODEs

Week #15 (Dec. 4) 
Thursday 
Fractals

Week #16 (Dec. 12) 
Homework assignments
Homework projects are officially due at 5PM on the dates listed below, but will be accepted until two days after, without a late penalty. So, if the homework is officially due on Friday at 5PM, you have until Sunday at 5PM to turn it in without penalty. A penalty of 10% will be incurred for every two days your homework is beyond the grace period deadline. You'll turn in your homeworks in your assigned Dropbox folders. Please read the Homework Tips before turning in your homework!
Homework #0 
Due Sep. 1

Homework #1 
Due Sept. 8

Homework #2 
Due Sept. 29

Homework #3 
Due Oct. 13

Homework #4 
Due 10/27

Homework #5 
Due Nov. 28

Homework #6 
Due Dec. 12

Matlab Tutorials
An online tutorial for this course, including all of the inclass labs can be found at the link below
Final Project
Our final activity will be a quiz during the day of our final
Grading policy
Homework projects (including the final activity) will count for 80% of your final grade, quizzes will count towards 20% of your grade. All homeworks will be equally weighted.