Details of MA4204 (Spring 2021)

Level: 4 Type: Theory Credits: 4.0

Course CodeCourse NameInstructor(s)
MA4204 Probability II Anirvan Chakraborty

Syllabus
Quick review of concepts and results (without proof) from basic discrete and continuous random variables, 1-1 correspondence between distribution functions and probabilities on $\mathbbR$, examples of probability measures in Euclidean space, a metric on the space of probability measures on $\mathbbR^d$, expectation and the convergence theorems, independence, Borel-Cantelli lemma, weak and strong laws in the $iid$ cases, Kolmogorov's 0-1 law and three-series theorem, various modes of convergence, infinite products, Kolmogorov's consistency theorem, characteristic functions, uniqueness, inversion theorem, Levy continuity theorem, proof of CLT for the $iid$ case with finite variance, martingales, infinitely divisible laws and stable laws.

Prerequisite
Analysis IV (MA3204) and Topology (MA3201).

References
Suggested Texts:

1)Athreya, K.B. and Lahiri, S.N., Measure Theory and Probability Theory, Springer.
2)Ash, R. and Dolans-Dade, C.A., Probability and Measure Theory, Academic Press
3)Billingsley, P., Probability and Measure, John Wiley.
4)Borkar, V.S., Probability Theory : An Advanced Course, Springer.
5)Chung, K.L., A Course in Probability Theory, Elsevier.
6)Durrett, R., Probability : Theory and Examples, Cambridge University Press.
7)Gut, A., Probability : A Graduate Course, Springer.
8)Lo\`eve, M., Probability Theory, Vols. I \& II, Springer.
9)Parthasarathy, K.R., Introduction to Probability and Measure, Hindustan Book Agency.

Course Credit Options

Sl. No.ProgrammeSemester NoCourse Choice
1 IP 2 Not Allowed
2 IP 4 Elective
3 IP 6 Not Allowed
4 MR 2 Not Allowed
5 MR 4 Not Allowed
6 MS 10 Not Allowed
7 MS 4 Not Allowed
8 MS 6 Not Allowed
9 MS 8 Elective
10 RS 1 Not Allowed
11 RS 2 Elective