Lectures schedule (L01)

Tutorials schedule (T01)

Monday/Wednesday/Friday
15:0015:50 (MS 217)

None 
Midterm and Quizzes:
There will be 1 Midterm (October 31 Monday, 15:00am, MS 217)
and 2 Quizzes (Mondays, October 3 and November 28, 15:00am, MS
217).
Final Exam:
Saturday, December 17, 810 am, ST 131
It will cover all the materials covered in this
course.
Grading scheme (Course Evaluation):
Exam, Midterm, Quizzes and
Homework Assignments

Value (% of your final mark)

Dates

Midterm

30%

Oct 31, 2015, Monday,
15:00, MS 217 
Quizzes (2)

20%=2x10%

Oct 3 &
Nov 28, Monday, 15:00, MS 217 
Final Exam  50%  Saturday,
December 17, 810am, ST 131 
Homework Assignments 
Not for Credit but for your
practice 
Month 
Day 
Monday 
Day 
Wednesday 
Day 
Friday 

Sep 
12 
Lec1: Intro to Probability Theory (Appendix: Basic in Probability) 
14 
Lec2:
Stochastic Processes (2.9) 
16 
Lec3:
Markov Chains (MC): Introduction (4.1) 

Sep 
19 
Lec4: MC: ChapmanKolmogorov Equations (4.2)  21 
Lec5: MC: Classification of States (4.3): Accessible States, Classes, Irreducible MC  23 
Lec6: MC: Classification of States (4.3): Recurrent and Transient States; Random Walk  
Sep 
26 
Lec7: MC: Limiting Probabilities (4.4)  28 
Lec8: MC: Limiting Probabilities. ExampleInsurance Claim (4.4) (cont'd Lec7)  30 
Lec9: MC: Some Applications (4.5)  
Oct 
3 
Quiz#1 (based
on Lectures 18) 
5 
Lec10: MC: Mean Time Spent in Transient States (4.6)  7 
Lec11: Exponential distribution (5.2.1)  
Oct 
10 
Thanksgiving Day
(No Lecture) 
12 
Lec12: PP: Counting Process ( 5.3.1) and Definition of PP (5.3.2)  14 
Lec13: PP: Waiting Time Distribution (5.3.3)  
Oct 
17 
Lec14: PP: Further Properties (5.3.4)  19 
Lec15: PP: Conditional Distribution of Arrival Times (5.3.5)  21 
Lec16: PP: Sampling of PP (5.3.5)  
Oct 
24 
Lec17: PP: Generalizations (5.4.1)  26 
Lec18: PP: Compound PP (5.4.2)  28 
Lec19: PP: Mixed PP (5.4.3)  
OctNov 
31 
MIDTERM
(based on Lectures 118) 
2 
Lec20: Continuoustime Markov Chains (CTMC): Intro (6.16.2)  4 
Lec21: CTMC: Birth& Death Processes (6.3) and Transition Probability Function (6.4)  
Nov 
7 
Lec22: CTMC: ChapmanKolmogorov Equations (6.4)  9 
Lec23: CTMC:
Limiting Probabilities (6.5) 
11 
Reading Day (No Lecture) 

Nov 
14 
Lec24: CTMC: Computing the Transition Probabilities (6.8)  16 
Lec25: Renewal
Theory: Intro (7.1), Renewal Process, Properties

18 
Lec26: Renewal Theory: Some Distributions (7.2),
Renewal Equation. 

Nov 
21 
Lec27: Renewal Theory: Limit Theorems (7.3)  23 
Lec28: Brownian Motion (BM) (10.1); Variations and Martingales Properties (10.3)  25 
Lec29: BM: Pricing Stock Options and BlackScholes Formula (10.4.110.4.2)  
Nov 
28 
Quiz#2 (based on Lectures
2029) 
30 
Lec30: BM: BlackScholes Formula's Derivation  2 
Lec31: BM: BlackScholes Formula's Interpretation  
Dec 
5 
Lec32: Stationary Processes (10.7)  7 
Lec33: Simulation Methods
(11.211.3) Table of Random Digits 
9 
Lec34:
Course Review. 
Marks for Stat 507 Formula Sheet and Tables for Final Exam Office Hours before the Final Exam: T122pm, TR1:303pm, Friday121pm 
Homework
Assignments Solutions to Chapters 2  10 TND TEF 