Scientific Computing with Matlab (Math 365)
In this course, we will learn how to use Matlab for applying computational methods to solving problems from science and engineering. 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.
 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  Monday/Wednesday 1:302:45 and 3:004:15 
Place  B210 (Riverfront Building) 
Office Hours  Wednesday 4:30PM5:30PM 
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 (Jan. 12) 
Monday 
Introduction to Scientific Computing
Wednesday 
Assigning Variables; Tips for doing Homework #0

Week #2 (Jan. 19) 
Monday 
Martin Luther King Day (no class)
Wednesday 
Creating 1d plots in Matlab

Week #3 (Jan. 26) 
Wednesday 
Quiz #1; The forloop and 2d arrays

Week #4 (Feb. 2) 
Monday 
2d arrays (continued)
Wednesday 
Solving linear systems

Week #5 (Feb. 9) 
Monday 
Gaussian Elimination
Wednesday 
Quiz #2; Gaussian Elimination

Week #6 (Feb. 16) 
Monday (no class) 
President's Day
Wednesday (no class) 
Timing a linear solve

Week #7 (Feb. 23) 
Monday 
Timing operations in Matlab
Wednesday 
Accuracy of the temperature equation u''(x)=f(x)

Week #8 (Mar. 2) 
Monday 
Fitting curves to data

Week #9 (Mar. 9)  
Week #10 (Mar. 16) 
Monday (no class) 
Wednesday (no class) 
Barycentric Formula

Week #11 (Mar. 30) 
Monday 
Wednesday 

Week #12 (Apr. 6) 
Wednesday 
Piecewise polynomial interpolation (cont)

Week #13 (Apr. 13)  
Week #14 (Apr. 20) 
Monday 
Function minimization : The Golden line search method; fminbnd

Week #15 (Apr. 27) 
Wednesday 
Solving ordinary differential equations

Homework assignments
Homework projects are officially due on the Wednesday due date at 5PM, but
will be accepted until Friday 5PM, without a late penalty. A penalty of 10% will be
incurred for every two days your homework is late.
You'll turn in your homeworks in your assigned Dropbox folders. Unless
otherwise stated, homeworks will all be turned in individually.
Please read the
Homework Tips
before turning in your homework!
Homework #0 
Due Jan. 21

Homework #1 
Due Feb. 4

Homework #2 
Due Feb. 25

Homework #3 
Due Mar. 11

Homework #4 
Due Apr. 1

Homework #5 
Due Apr. 15

Homework #6 
Due Apr. 29

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.