Scientific Computing with Matlab (Math 365)
In this course, we will learn how to use Matlab to solve problems in science and engineernig 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 intially.
 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  Wednesday/Friday 10:30AM11:45AM 
Place  MG136 (Math Computing Lab) 
Office Hours  Wednesday 2:30PM4:30PM 
Prerequesites  Math 175 
Recommended and suggested textbooks
 Numerical Computing with Matlab, by Cleve Moler. Mathworks, Inc., (2004) (required).
 Matlab software, by Mathworks, Inc.. (required).
 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. 24) 
Wednesday 
Introduction to Scientific Computing
Friday 
Assigning Variables; Tips for doing Homework #0

Week #2 (Aug. 31) 
Wednesday 
Friday 
Creating 1d plots in Matlab

Week #3 (9/7) 
Wednesday 
1d Arrays (continued)
Friday 
The forloop and 2d arrays

Week #4 (Sept. 14) 
Friday 
Solving linear systems

Week #5 (Sept. 21) 
Wednesday 
Using linear algebra to solve a circuit problem
Friday 
Floating point arithmetic

Week #6 (Sept. 28) 
Wednesday 
Floating point arithmetic (continued)
Friday 
Numerical conditioning

Week #7 (Oct. 5) 
Wednesday 
Vandermonde Matrix System
Friday 
Lagrange polynomials

Week #8 (Oct. 12) 
Wednesday 
Fitting curves to data
Friday 
The Barycentric Formula

Week #9 (Oct. 19) 
Wednesday 
Curve fitting
Friday 

Week #10 (Oct. 26) 
Wednesday 

Week #11 (Nov. 2) 
Wednesday 
Explanation of roller coaster problem
Friday 
Newton's method and Fractals

Week #12 (Nov. 9) 
Wednesday 
Rootfinding using fzero

Week #13 (Nov. 16) 
Wednesday 
Errors in quadrature formulas

Week #14 (Nov. 30) 
Wednesday 
Friday 

Week #15 (Dec. 7) 
Wednesday 
Friday 

Homework assignments
Homework projects are officially due on the Friday due date at 5PM, but
will be accepted until Sunday 5PM, without a late penalty. A penalty of 10% will be
incurred for every two days your homework is beyond the final Sunday deadline.
You'll turn in your homeworks in your assigned Dropbox folders.
You may work individually on the assignment, or in teams of two.
Please read the
Homework Tips
before turning in your homework!
Homework #0 
Due Friday, Sept. 4

Homework #1 
Due Sept. 11

Homework #2 
Due Sept. 25

Homework #3 
Due Oct. 9th

Homework #4 
Due Oct. 23

Homework #5 
Due Nov. 6th

Homework #6 
Due Nov. 20th

Matlab Tutorials
An online tutorial for this course, including all of the inclass labs can be found at the link below
Final Project
In lieu of a final, you will have a final project due, on the day of our scheduled exam.
 Other resources :
 final_project.pdf  Final project description
You can find the Final Exam calendar here.
Grading policy
Homework projects will count for 60% of your final grade, quizzes will count towards 20% of your grade, and the final project will be 20% of your final grade. All homeworks will be equally weighted.