Probability Models and Applications (ERG2040C)
Student/Faculty Expectations on Teaching and Learning
Student/Faculty Expectations on Teaching and Learning
Instructor:
John C.S. Lui
In this course, we cover fundamental principles of probability
theory, and to learn
how to use this framework (or methodology) to have logical thinking
and carry out analysis to computer science and engineering problems.
Note that this course is "conceptual" and "mathematical"
in nature. Students need to spend the time to read the textbook,
do the homework, attend the lectures and tutorials so
to understand and keep pace with the expectation of this course.
Teaching Assistants (HSH Eng. Bldg, Room 120):
Textbook:
A First Course in Probability (8th Edition), by Sheldon Ross
Course Grades:
 Homework: 25%;
 Programming or simulation: 25%;
 Examination: 50% (note: you need to get at least 25% in the exam to pass the course)
Policy: Late homework, programming or simulation will NOT be
considered.
Course Schedule (2nd term, 2011):
 Lecture:
 Tuesday: 5:306:15 PM (LSB LT6);
 Thursday: 12:302:15 PM (MMW LT2);
 Tutorial:
 Monday: 12:301:15 (LPN LT);
 Monday: 1:302:15 PM (LHC G04); TSA;
 Monday: 4:305:15 PM (ERB 703); TSA;
Newsgroup:
Please visit the following newsgroup: cuhk.cse.engg2040c,
for any announcement. Students can also post
comments/questions in the newsgroup.
Students can access the newsgroup via:
 tin (terminal interface),
 thunderbird,
 outlook.
The tentative outline for the course:
 Introduction: why probability theory?
 Combinatorial Analysis
 Axioms of Probability
 Conditional Probability and Independence
 Random Variables: discrete vs. continuous
 Joint Distributed Random Variables
 Expectations and their Properties
 Law of Large Numbers and Limit Theorems
 Markov Processes (*)
 Maximum Likelihood and Hypothesis Testing (*)
 Monte Carlo Simulation
Lecture Notes (note: all lecture notes are password protected)

Preliminary Administrative Information and Mutual Expectations

Introduction: why study probability?

Combinatorial Analysis
(Reading Assignment: Chapter 1)

Axioms of Probability (part 1)
(Reading Assignment: Chapter 2)

Axioms of Probability (part 2)
(Reading Assignment: Chapter 2)

Conditional Probability
(Reading Assignment: Chapter 3)

Conditional Probability (Part II)
(Reading Assignment: Chapter 3)

Random Variables (Part I)
(Reading Assignment: Chapter 4)

Random Variables (Part II)
(Reading Assignment: Chapter 4)

Continuous Random Variables (Part I)
(Reading Assignment: Chapter 5)

Continuous Random Variables (Part II)
(Reading Assignment: Chapter 5)

Jointly Distributed Random Variables (Part I)
(Reading Assignment: Chapter 6)

Jointly Distributed Random Variables (Part II)
(Reading Assignment: Chapter 6)

Limit Theorems
(Reading Assignment: Chapter 8)
Tutorial Notes

Tutorial 1

Tutorial 2

Tutorial 3

Tutorial 4: Monte Carlo Simulation

Tutorial 5: Monte Carlo Simulation 2 ;
Java Program on Monte Carlo Simulation ;

Tutorial 6

Tutorial 7

Tutorial 8

Tutorial 9

Tutorial 10

Tutorial 11

Tutorial 12

Tutorial 13

To be added
Homework (students can submit their homework in the drop box, 10/F, HSH Eng. Bldg)

Homework 1 ;
Solution to Homework 1

Homework 2 ;
Solution to Homework 2

Homework 3 ;
Solution to Homework 3

Homework 4 ;
Solution to Homework 4

Homework 5 ;
Solution to Homework 5
Project

Monte Carlo Simulation ;
(Programming Assignment is announced !!!) ;
Instruction on how to submit the programming assignment ;