MATH 318 Probability with Physical Applications
2014 Winter Term II
Instructor: Daniel Valesin
Mon Wed Fri 14:00-15:00
Room: Buchanan A201
- 6/Jan - The course is starting! Assignment 1 and Octave tutorial exercise with solutions posted. If you are not familiar with Octave or Matlab, make sure to read the section "GNU Octave" below.
- 8/Jan - I will be away this Friday (10/Jan). Lecture will take place at the usual time with a substitute instructor, but office hours are cancelled. On Monday everything will be back to normal.
- 20/Jan - I will be away on Wednesday and Friday (22/Jan and 24/Jan). Lectures will take place at the usual times with a substitute instructor, but office hours on Friday are cancelled. I will schedule extra office hours next week. Additionally, the due date for Assignment 3 has been postponed to Friday, 31/Jan.
- 27/Jan - Extra office hours this week: Thursday 30/Jan, 9-11am at LSK303C.
- 28/Jan - Midterm 1 next Monday. Material: everything covered in class up to (and including) variance. No cheat sheets allowed.
- 4/Feb - Solutions to Midterm 1 posted (the actual midterm is here).
- 12/Feb - Bonus Assingment posted. This is an optional set of exercises worth 3% extra points on the final course grade. Incomplete assignments will not be considered; you should work on every question. Due date is Wednesday, March 5.
- 15/Mar - Solutions to Midterm 2 posted (the actual midterm is here).
- 30/Mar - Assignment 8 is due on Wednesday, April 2.
- Review exercises and solutions posted.
There will be nine homework assignments:
Assignment 1. Solutions
Assignment 2. Solutions
Assignment 3 . Solutions
Assignment 4 . Solutions
Assignment 5 . Solutions
Assignment 6 . Solutions
Assignment 7 . Solutions
Assignment 8 . Solutions
Assignment 9 . Solutions
Some of these notes are based on lecture notes by Prof Gordon Slade. If you find typos or mistakes in the notes, please let me know immediately.
Lectures 1, 2 and 3
Lectures 4, 5 and 6
Lectures 7, 8 and 9
Lectures 10, 11 and 12
Lectures 13, 14, 15 and 16
Lectures 17, 18 and 19
Lectures 20, 21 and 22
Lectures 23 and 24
Lectures 25, 26 and 27
Lectures 28, 29 and 30
Lectures 31, 32 and 33
Review exercises (solutions)
COURSE OUTLINE AND SCHEDULE
Introduction to Probability Models, 10th edition
by Sheldon Ross. Feel free to use the 9th edition, but homework
problems will be assigned only from the 10th edition.
10% - Homework
20% - Midterm 1. Solutions
20% - Midterm 2. Solutions
50% - Final exam
Both midterms will occur during class time, and hence their duration will be 50 minutes. Their dates will be:
I will announce the corresponding topics here some weeks in advance.
- Midterm 1: Monday 03/Feb
- Midterm 2: Friday 14/Mar
Mondays 10:00-12:00 and Fridays 11:00-12:00 at room LSK303C
PREREQUISITE FOR MATH 318
You must have taken one of MATH 152, MATH 221, MATH 223 and also one of
MATH 215, MATH 255, MATH 256, MATH 265, and you must either have taken or currently be taking
one of MATH 256, MATH 257, MATH 267, MATH 316. You cannot receive credit for this course as well
as credit for any one of MATH 302, MATH 303, STAT 241, STAT 251, STAT 302, COMM 290.
An important part of the course is the development of computer simulations of probability models. Many of the assigments, and possibly the exams, will include simulation exercises.
Our preferred tool for writing simulations will be GNU Octave. You are also allowed to use Matlab, which will be almost identical to Octave for our purposes. As soon as the course begins, you should download and install Octave (or Matlab) in your computer (Octave is free; Matlab is not). Even if you have no previous experience with either of these languages, or with computer programming, it should be easy to learn what is needed. In particular, we'll need a few commands for generating random numbers and plotting graphs and a very basic understanding of algorithms (conditional clauses, loops etc.)
Guide to Octave: If you have never worked with Octave or Matlab before, take a look at this guide by P. J. G. Long. Reading pages 5-22 and 25-38 is more than enough.
Tutorial exercise: Here is a tutorial exercise which will require you to use many of the commands we'll need throughout the course. This zip file contains the solutions for the tutorial.