Lectures schedule (L01)

Tutorials schedule (T01)

Monday/Wednesday/Friday
15:0015:50 (SS
113)

None 
Midterm and Quizzes:
There will be 1
Midterm (October 29 Monday, 15:00am, SS 113)
and 2 Quizzes (Mondays, October 1 and November 26, 15:00am, SS 113).
Final Exam: Tuesday,
December 11, 7pm9pm (roomTBA)
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 29, 2018, Monday, 15:00, SS 113 
Quizzes (2)

20%=2x10%

Oct 1 & Nov 26, 2018, Monday, 15:00, SS 113 
Final Exam  50%  Tuesday,
Decmber 11, 7pm9pm (roomTBA) 
Homework Assignments 
Not for Credit but for your
practice 
Month 
Day 
Monday 
Day 
Wednesday 
Day 
Friday 

Sep 
7&10 
Lec1 (Friday, Sept 7)Lec2 (Monday, Sept 10): Intro to
Probability Theory (Complimentary Notes: Basics in Probability) 
12 
Lec2: Stochastic
Processes (2.9) 
14 
Lec3: Markov
Chains (MC): Introduction (4.1) 

Sep 
17 
Lec4: MC: ChapmanKolmogorov Equations (4.2)  19 
Lec5: MC: Classification of States (4.3): Accessible States, Classes, Irreducible MC  21 
Lec6: MC: Classification of States (4.3): Recurrent and Transient States; Random Walk  
Sep 
24 
Lec7: MC: Limiting Probabilities (4.4)  26 
Lec8: MC: Limiting Probabilities. ExampleInsurance Claim (4.4) (cont'd Lec7)  28 
Lec9: MC: Some Applications (4.5)  
Oct 
1 
Quiz#1 (based
on Lectures 19) 
3 
Lec10: MC: Mean Time Spent in Transient States (4.6)  5 
Lec11: Exponential distribution (5.2.1)  
Oct 
8 
Thanksgiving Day
(No Lecture) 
10 
Lec12: Poisson Process (PP): Counting Process ( 5.3.1) and Definition of PP (5.3.2)  12 
Lec13: PP: Waiting Time Distribution (5.3.3)  
Oct 
15 
Lec14: PP: Further Properties (5.3.4)  17 
Lec15: PP: Conditional Distribution of Arrival Times (5.3.5)  19 
Lec16: PP: Sampling of PP (5.3.5)  
Oct 
22 
Lec17: PP: Generalizations (5.4.1)  24 
Lec18: PP: Compound PP (5.4.2)  26 
Lec19: PP: Mixed PP (5.4.3)  
OctNov 
29 
MIDTERM (based
on Lectures 118) 
31 
Lec20: Continuoustime Markov Chains (CTMC): Intro (6.16.2)  2 
Lec21: CTMC: Birth& Death Processes (6.3) and Transition Probability Function (6.4)  
Nov 
5 
Lec22: CTMC: ChapmanKolmogorov Equations (6.4)  7 
Lec23: : CTMC: Limiting Probabilities (6.5) 
9 
Lec24: CTMC: Computing the
Transition Probabilities (6.8) 

Nov 
13 
Fall Break  15 
Fall Break  17 
Fall Break  
Nov 
19 
Lec25: Renewal Theory: Intro (7.1), Renewal
Process, Properties. 
21 
Lec26: Renewal Theory: Some Distributions
(7.2), Renewal Equation. Limit Theorems (Optional)(7.3) 
23 
Lec27: Brownian Motion (BM) (10.1);Variations and Martingales
Properties (10.3) 

Nov 
26 
Quiz#2 (based
on Lectures 2027) 
28 
Lec28: BM: Pricing Stock Options and BlackScholes Formula (10.4.110.4.2)  30 
Lec29: BM: BlackScholes Formula's
Derivation 

Dec 
3 
Lec30: BM: BlackScholes Formula's
Interpretation 
5 
Lec31: Stationary Processes (10.7)  7 
Lec32: Simulation Methods
(11.211.3) Table of Random Digits 
Midterm:
Monday, October 29, 3:003:50pm, SS 113
(based on Lectures 118; No Aids; Basic Calculator is Allowed) * Final Exam: Tuesday, December 11, 7pm9pm (roomTBA) * Please, use your @ucalgary.ca email to communicate with your instructor 
Homework Assignments (Solutions to Chapters 2&4) Laplace Table TableNormalDistribution TableExponentialFunction 