COURSE COVERAGE
Date  Coverage  Homework 

Jan. 5  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. 7  MEET IN GAUSS LAB (you will need
an activated AML account or laptop)

Complete all six chapters of the datacamp course. I will check that
you've done them at the beginning of class on Tuesday. We will meet in
the Gauss Lab again. ALSO:

Jan. 12 


Jan. 14 
Today you will:


Jan. 19  We went over Chapter 2 in the textbook.  To be able to participate in the next class, please read before next
lecture:

Jan. 21  Today, we will go over how to write R functions together. You will then work on the next inclass assignment, based on chapter 2 work. You should use functions that you write to solve this problem set. We will do this over two classes, as I want to present some minor additional material for exercises 6 and 7, which I will do next Tuesday. Next Tuesday I will check that you have completed at least four of the eight problems though. 

Jan. 26 
Plan for today:

We will continue working on the assignment this Thursday inclass. I expect you to have tried all the questions though before coming to class. The actual assignment will be due Sunday night. 
Jan. 28 
Plan for today:

DUE: Monday, February 1st at midnight. Please hand in your complete assignment in R script and scanned written pages (if need by) by email no later than midnight on Monday. Late assignments will receive a grade of zero. 
Feb. 2  Chapter 3 lecture along with examples.  
Feb. 4 

DUE: Friday, February 5th before midnight. Hand in short inclass assignment via email. Late assignments will receive a grade of zero. 
Feb. 9  Recently, we have been talking about "basic" Monte Carlo  using sample averages to estimate integrals. The next topic will be looking at convergence diagnostics for this Monte Carlo method (so far, we have only the one). A small part of these diagnostics is the bootstrap  which we haven't covered yet. Therefore, we will now take a break to consider the bootstrap, before returning to Monte Carlo.  
Feb. 11 
Today, you will work on inclass assignment on the
bootstrap. For this you will need:


Feb. 1519  READING WEEK 
DUE: Friday, February 19th by midnight:

Feb. 23  RaoBlackwellization (reference: Section 4.6)  
Feb. 25  Stratified sampling. Comparing estimators via a simulation study.  Reference: [PDF] 
March 1  Work on these inclass assignments:  
March 3  TEST ONE  
March 8  We will continue working on the latest batch of inclass assignments today.  Go over as much of the assignments at home as you can, so that on Thursday (last day of inclass time) you can resolve any outstanding problems. 
March 10  Last day to work on inclass on RaoBlackwell, stratification, and importance sampling comparisons.  DUE: Monday, March 14th at midnight. 
March 15  MCMC lectures by Prof. Peskun  
March 17  MCMC lectures by Prof. Peskun  
March 22  MCMC inclass assignment. Meet in GAUSS LAB. Assignment will be handed out in class!  
March 24  class is cancelled  
March 29  Inclass permutation assignment (due end of class): Watch this. PLEASE BRING A SET OF HEADPHONES if you can. The data can be found here. You may also find this useful (section 2). This is due by 11:20 am today.  
March 31  TEST TWO (in TEL) 