COURSE COVERAGE
Date  Coverage  Homework 

Jan. 4  Review of some undergraduate probability basics: RVs, CDF/PDF/PMF, expectation, LLN and CLT. If you're weak on this stuff, my favourite reference is "Mathematical Statistics and Data Analysis" by Rice. Great book.  
Jan. 9 
MEET IN GAUSS LAB (Ross S110)!

ASSIGNMENT ONE: Complete data camp assignment (all) for January
11th at 10am.

Jan. 11  Confidence intervals and their meaning; empirical cumulative distribution function and the GlivenkoCantelli Lemma. Also looked at examples in R. [PDF]  
Jan. 16  More review: qq plots. [PDF]  Work on the questions in the script. Together with the questions on the CI/ECDF scripts, these will make up your next assignment (due date TBA). Make sure that you are (a) understanding the nature of the output, (b) going over the code and asking questions any time you're unsure of something. 
Jan. 18  Class cancelled due to personal emergency.  
Jan. 23  Today we will go over the two remaining scripts in detail, and
you will have more time to work on the questions  and more
importantly sort out any questions you have regarding the code.

N.B. Today's shutdown snafu should not repeat again. I talked to our friendly IT guy, and this was just a mistake. HOWEVER, this shutdown has to happen before each class on T/R at 11:30, so he has scheduled it for every T/R at 11:22am. Thus, make sure you save your work before this time at the end of each class in the future! 
Jan. 25 


Jan. 30  Chapter 2, generating RVs: pseudorandom numbers, inverse transform, special tricks, BoxMuller, the multivariate normal. 
In class we talked briefly about pseudorandom number generators.

Feb. 1  [R script] for today.


Feb. 6  Contine working on questions form chapter 2 script [R script]. You'll need the textbook for this.  Continue working on the questions  you will have one more class day to resolve outstanding issues, so you should try all questions prior to next Thursday morning. 
Feb. 8  Continue working on questions from chapter 2 script. This is the last day for this.  
Feb. 13  Introductory lecture to Monte Carlo, followed by [R script]. 

Feb. 15  Basic MC; importance sampling; sampling importance resampling; followed by [R script]. After the lecture, proceed with the questions in the script. I will be checking (and marking) your progress. 

Feb. 1723  READING WEEK  Assignment 3 is due at 10am on Tuesday 
Feb. 27  Stratified sampling lecture. 

March 1 

STUDY! Also, work on the assignment. 
March 6  TEST ONE  Work on the most recently assignment and other scripts. 
March 8  Inclass time to continue working on most recent assignment.  
March 13  The bootstrap: 
Today we covered the basics of the bootstrap (parametric and
nonparametric) to calculate the bootstrap distribution, bootstrap se,
bootstrap percentile/pivotal CIs, boostrap bias estimate.
References for the bootstrap: [PDF][PDF] (imho the friendliest read is Section 2.8 of the second reference. We only covered enough background to do go through the R script.) Homework: [PDF] N.B. You will need more info and data to complete all of the exercises, but for now you can get started. The additional details will be provided for next class. 
March 15 

Assignment 4 is due today at midnight. Please see the announcements page for details on exactly what you need to hand in. 
March 20  Introduction to stochastic optimization:

Today we went over "basic" stochastic optimization (roughly, the first paragarph of Section 5.3.1), and reviewed other options for optimization both in R and otherwise that we have used in this course. We went over the R scripts in detail. 
March 22  Last day of coverage for test two!


March 27 

Read Section 5.3.2 and 5.3.3 from the textbook. 
March 29  TEST TWO  Work on your assignments (A5 and A6)  in particular, there will be time to get any simulated annealing issues dealt with on April 3rd. 
April 3 
