Course Archives    Theoretical Statistics and Mathematics Unit
Course: Topics in Applied Stochastic Processes
Instructor: Mathew Joseph
Room: Physics Lab
Level: Undergraduate
Time: Currently offered
Syllabus
Past Exams


Syllabus: Discrete parameter martingales (without conditional expectation w.r.t. algebras), Branching processes, Markov models for epidemics, Queueing models.
Notes: (i) Measure theory to be avoided. Of course, use of DCT, MCT, Fubini, etc. overtly or covertly permitted. (ii) Relevant materials concerning Markov chains, including continuous time MCs, may be reviewed. If this course runs concurrently with Prob. III (where Markov chains are taught), some concepts/facts needed may be stated with proofs deferred to Prob. III. (iii) Genetic models may also be included, but then at least two topics from the above may have to deleted, as the background material from genetics may be formidable.

Reference Texts:

1. A. Goswami and B. V. Rao: A Course in Applied Stochastic Processes. Hindustan Book Agency
2. S. Karlin and H. M. Taylor: A First and Second Course in Stochastic Processes. Academic Press, 1975 and 1981.
3. S. M. Ross: Introduction to Probability Models.8th edition.Academic Press/Elsevier, Indian reprint, 2005. (Paperback) 4. S. M. Ross: Stochastic Processes. 2nd edition. Wiley Student Edition, 2004. (Pa-perback)

Evaluation:
Midterm Exam 30 marks
Assignment 20 marks
Final Exam 50 marks
Total 100 marks


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Past Exams
Midterm
Semestral
Supplementary and Back Paper

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