Instructor 
Syllabus 
Office Hours 


 Monday (35)
 Tuesday (13)
 Thursday (111, 35)

Homework Assignments & R Code/Data
Assignment 
Due Date 
R 
Homework #1 
Wednesday, February 4 

Homework #2 
Wednesday, February 11 
hw2.r 
Homework #3 
Wednesday, February 18 
hw3.r 
Homework #4 
Wednesday, February 25 
awaywin.txt hw4.r 
Homework #5 
Wednesday, March 11 

Homework #6 
Wednesday, March 18 
hw6.r 
Homework #7 
Wednesday, March 25 
hw7.r cherry.txt 
Homework #8 
Wednesday, April 15 

Homework #9 
Friday, April 24 
hw9.r 
Homework #10 
Wednesday, April 29 

Homework #11 
Wednesday, May 6 

Recorded Lecture  March 19
Homework Solutions

Course Handouts
Chapter 
Handout 
R Script 


R Introduction 


Distributions and Their Properties 

3,4,5 
Review of Chapter 3,4,5 Material 

6.1,6.2 
The Law of Large Numbers 
lawlarge.r 
6.3,6.4 
The Central Limit Theorem 

7.17.5 
Estimation Methods 
betabinomial.r 
7.6 
Properties of MLEs 


Review Sheet  Test #1 
7.77.8 
Sufficient Statistics 

7.9 
Improving Estimators 

8.18.4 
Sampling Distributions 

8.5 
Confidence Interval Estimation 


Review Sheet  Test #2 

Monte Carlo Confidence Interval Examples 
moncarlo.r 
8.7,8.8 
Unbiased Estimators and the CRLB 

6.3,8.8,other 
Variance Approximations 


Bootstrapping and Applications (Not in book) 
bootstrap.r 
9.1,9.2 
Hypothesis Testing (9.19.2) 

9.1,9.5 
Likelihood Ratio Test Examples 


Review Sheet  Test #3 
9.2,9.3 
The NeymanPearson Lemma 

9.2,9.3 
More on the NeymanPearson Lemma 


Review Sheet  Final Exam 

Not in book 
Markov chain Monte Carlo Methods 

