INDIAN STATISTICAL INSTITUTE
7 S. J. S. Sansanwal Marg, New Delhi 110016
Measure Theoretic Probability
M.Stat. (NB-Stream) Ist Year and MS(QE) IInd Year
Academic Year 2017 - 2018: Semester II
Instructor: Antar Bandyopadhyay
Email: antar (at) isid (dot) ac (dot) in
Office: Room # 208 on the first floor of the Faculty Block.
Instructor's Office Hours: Monday and Thursday 1:15 PM - 2:15 PM
Teaching Assistant (TA): Partha Pratim Ghosh
Email: p (dot) pratim (dot) 10 (dot) 93 (at) gmail (dot) com
TA's Office Hours: Tuesday 4:00 PM - 6:00 PM in the Research Scholar's Lab
Class Time: (2 x 120 minutes per week)
During the Weeks 01 to 02 Monday & Thursday: 05:30 PM - 07:30 PM
During the Weeks 03 to 07 Monday & Thursday: 09:15 AM - 11:15 AM
During the Weeks 09 to 15 Monday & Thursday: 11:00 AM - 01:00 PM
Lecture Hall: Room # 23 Academic Block (First Floor).
Course Duration (including examinations): January 08 - May 04, 2018
(Total of 17 Weeks = 7 Weeks of Classes + 1 Midterm Examination Week + 7 Weeks of Classes + 2 Final Examination Weeks).
Date: Thursday, March 01, 2018
Duration: 10:00 AM - 12:00 noon (Two Hours)
Venue: Conference Hall, First Floor, Administrative Block
Date: TBA (during April 23 - May 04, 2018)
Duration: 10:00 AM - 01:00 PM (Three Hours)
Venue: Conference Hall, First Floor, Administrative Block
- Basic Measure Theory:
- Review of the notion of cardinality of sets, finite, countable, uncountable sets.
- Algebra of sets, σ-algebra, examples, Borel σ-algebra.
- Monotone classes, π-systems, λ-systems. Monotone Class Theorem
and Dinkin's π-λ Theorem. Uniqueness theorems.
- Measurable functions, sum, product, maximum, minimum of measurable
functions. Limits of measurable functions. Random variables,
simple functions, Monotone Approximation Theorem.
- Definition of measure, set functions, finite and countable additivity.
Finite and infinite measures, probability measures, basic laws of
measures. σ-finite measures.
- Existence and extension theorems. Outer measure,
Carathéodory's Extension Theorem.
Construction of the Lebesgue
measure on unit interval, real line and d-dimensional Euclidean space.
Properties of the Lebesgue measure.
- Distribution function, inverse distribution function, the Fundamental
Theorem of Probability.
- Lebesgue Theory of Integration. MCT, Fatou's Lemma, DCT,
Schéffe's Theorem. Calculus of measure zero sets. Concept of
"almost surely (a.s)". Change of variable formula. Expectation of a
random variable, law of unconscious statistician.
- Product space, basic definitions, sections. Product measure, existence
and uniqueness. Fubini's Theorem, applications.
- Measure Theoretic Probability:
- Independence. Borel-Cantelli Lemmas. Tail σ-algebra, Kolmogorov's
- Various modes of convergence and their interrelations. WLLN, SLLN.
Fundamental Theorem of Statistics (Glivenko-Cantelli Lemma).
- Kolmogorov's maximal inequality and applications. Kolmogorov's Three Seres Theorem, proof of the sufficiency part.
- Characteristic functions, definition, examples. Moment expansion,
characteristics function for Normal distribution. Inversion formula,
uniqueness theorem, density formula.
- Revision of weak convergence, definition, representation theorem, Portmanteau Theorem. Hally-Bray Theorem, tightness.
- Characteristic functions and weak convergence, Lévy's Continuity Theorem (statement only).
- Central Limit Theorems: De Moiver-Laplace CLT, I.I.D. CLT, Lindeberg CLT,
Lyapounov's CLT, proofs using Lideberg CLT. Applications. Proof of Lindeberg CLT. Proof of the necessity
part of the Kolmogorov's Three Series Theorem.
- Probability and Measure by P. Billingsley.
- Probability: Theory and Examples by R. Durrett.
- Measure and Probability by S. Athreya and V. S. Sunder.
- Introduction to Probability and Measure by
K. R. Parthasarathy.
- Measure Theory by P. R. Halmos.
- Probability Theory, Vol - I & II by W. Feller.
- Real Analysis and Probability by R. B. Ash.
We will mostly follow Billingsley, only occasionally the others may
be needed. Though they are all very good and important sources to
learn measure theory/probability theory.
- Real Analysis (at the level of Principles of Mathematical Analysis,
- Liner Algebra (at the level of Finite Dimensional Vector Spaces,
P. R. Halmos).
- Basic Probability (at the level of Introduction to Probability Theory,
P. G. Hoel, S. C. Port and C. J. Stone).
- Assignments: 10% of the total credit.
- Quizzes: 15% of the total credit.
- Midterm Exam: 25% of the total credit.
- Final Exam: 50% of the total credit.
- There will be a total of 14 sets of homework assignments each
carrying a total of 10 points. The average of the 10 best assignment scores
will be taken for the final grading.
- The assignments will be given in class on every Thursday,
starting from January 11, 2018. Each
assignment will be due in class on the Thursday of the following week. For
example the first assignment is due on Thursday, January 18, 2018.
- Each assignment will be based on the course materials which will be covered in the
class in the week of the assignment.
- Late submission of an assignment will NOT BE ACCEPTED. If you
can not submit an assignment on time, don't worry about it and try to do
well in the others. It will not count in your final grade since you
have four extra assignments anyway.
- Graded assignments will be returned in the class an week after their
submission. For example, the assignment which is due on January 18, 2018
(Thursday) will be returned after grading on January 25, 2018 (Thursday).
- Click here
for downloading the assignments.
- There will be at least four
quizzes as surprise tests given in the
class. This means there shall be no pre-scheduling. A quiz will cover
materials done in the lectures given in the weeks prior to it.
- Each quiz will be of 15 points and will be of 30 minutes duration.
- Final grade for the quizzes will be (Best Score Before Midterm + Best Score Between Midterm and Final)/2.
- There will be NO supplementary quiz given for any student who
may miss a quiz for whatsoever reason. If you miss one then do not worry,
try doing well in the others.
- All quizzes will be part of the final grading.
- All quizzes will be closed note and closed book examinations.
- The Midterm and the Final Examinations will be
open notes examinations. That means, students will be allowed
to bring his/her own hand written notes, study materials, list of
theorems etc. But no printed or photocopied materials will be allowed.
- Any unfair means used by any students in the examinations will be dealt with the strictest
possible measures, as per the Institute rules. In particular, if any student is found to be
using any kind of unfair practice during any of the examinations (including the quizzes) then
he/she will be awarded ZERO in that examination.
- Regrading of homeworks or exams will only be undertaken in cases where, you believe there has been a
genuine error or misunderstanding. Please note that our primary aim in grading is consistency,
so that all students are treated the same; for this reason, we will not adjust the score of one student
on an issue of partial credit, unless the score allocated clearly deviates from the grading policy
we adopted for that problem.
- If you wish to request a regrading of a homework or exam, you must return it to the instructor
with a written note on a separate piece of paper explaining the problem.
- The entire assignment or the exam may be regraded, so be sure to check the solutions to ensure that your
overall score will go up after regrading.
- All such requests must be received within one week from the date on which the homework or exam was made
available for return.
Last modified January 22, 2018.