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, KN DANCE (KNA 163)
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, KN DANCE (KNA
163) 
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 
Final Exam: Tuesday, December 11, 7pm9pm, KN DANCE (KNA 163) (Office Hours: Monday, Dec 10, 1pm3pm, MS 552) (Bring in Your ID Card) It will cover all the materials covered in this course. Formula Sheet for Final Exam and Two Tables (Normal Distribution and Exponential Funaction) Basic Calculator is Allowed * Your Marks: Q1 & Q2 & Midterm & FINAL EXAM (Excel) * Please, use your @ucalgary.ca email to communicate with your instructor 
Homework Assignments (Solutions to Chapters 211) Laplace Table TableNormalDistribution TableExponentialFunction 