Course Archives Theoretical Statistics and Mathematics Unit
Course: Measure Theoretic Probability
Instructor: Yogeshwaran D
Room: G25
Time: Currently offered
Level: Postgraduate
Syllabus
Past Exams


Syllabus: Measure and Integration: Monotone Class Theorem, Probability and Measures, Construction of Lebesgue measure, Integration, Fatou Lemma, Monotone and DominatedConvergence Theorems, Radon- Nikodym theorem, product measures, Fubinis theorem.

Probability: (If needed, a quick review of concepts and results (without proof) from basic Discrete and Continuous Probabilty.) Distribution Functions of Probabilty Measures on R, Borel-Cantelli Lemma, Weak and Strong Laws of Large Numbers in i.i.d. case, various Modes of Convergende, Characteristic Functions, Uniqueness/Inversion/Levy Continuity Theorems, Proof of the Central Limit Theorem for i.i.d. case with Finite Variance.

Suggested Texts:
1. W. Rudin, Real and complex analysis, McGraw-Hill Book Co. (1987).
2. P. Billingsley, Probability and measure, John Wiley (1995).
3. K. R. Parthasarathy, Introduction to probability and measure, TRIM (33), Hindustan Book Agency (2005).
4. J. Nevue, Mathematical foundations of the calculus of probability, Holden- Day (1965).
5. I. K. Rana, An introduction to measure and integration, Narosa Publishing House (1997).

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


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Past Exams
Midterm
06.pdf 10.pdf 12.pdf 14.pdf 16.pdf 18.pdf
Semestral
06.pdf 10.pdf 12.pdf 14.pdf 16.pdf
Supplementary and Back Paper
14.pdf 16.pdf

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