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PROBABILITY THEORY
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Probability Theory
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Academic year 2015/2016
- Course ID
- MAT0034
- Teaching staff
- Prof. Laura Sacerdote
Prof. Federico Polito - Year
- 1st year
- Teaching period
- First semester
- Type
- D.M. 270 TAF B - Distinctive
- Credits/Recognition
- 9
- Course disciplinary sector (SSD)
- MAT/06 - probabilita' e statistica matematica
- Delivery
- Class Lecture
- Language
- English
- Attendance
- Mandatory
- Type of examination
- Written and oral
- Prerequisites
- An undergrauate level class in Probability and good knowledge of real analysis. Good abilities in elementary probabilistic problem solving are also necessary for the success in this class.
- Propedeutic for
- Stochastic Processes, Statistics for Stochastic Processes and EDS-Stochastic Dfferential Equations use concepts and tools introduced in this course.
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Sommario del corso
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Course objectives
Topics taught in this class are essential tools required to a statistician and a probabilist. They are fundamental for any modern mathematician. Students re-think to subjects of their undergraduate studies with a different level of abstraction.This new approach allows them to control some advanced methods of probability theory, useful for applications as wel as for research.
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Results of learning outcomes
Students attain a detailed knowledge of the foundations of the theory of probability and related topics in measure theory. They attain good ability in probabilistic problem solving becoming able to deal both with theoretical and applied problems related with conditional expectation, convergence features, characteristic functions and martingales.
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Course delivery
There will be 72 hours of lessons, including 16 hours of in class exercises. Personal training on assigned exercises is important for the success in this class.
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Learning assessment methods
Final exam includes written and an oral tests. The two tests are scheduled on different dates. The written test holds until the next oral exam Written test request the solution of two exercises and it is mandatory to pass this test to be admitted to the oral test.The oral examination includes a discussion on the written test as well as the answer to two question, taken at random by the student. Students can use textbook during the written test.
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Support activities
The course include exercises classes; extra exercises are suggested as homework.
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Program
Overview of elementary probability. Construction of probability measures on R and random variables. Integrals over probability measures. Independent random variables. Distributions on Rn. Sums of random variables. 0-1 Laws. Convergence of sequences of random variables. Weak convergence and characteristic functions. Laws of large numbers and central limit theorem. Conditional expectations. Discrete time martingales, optional stopping , Doob decomposition and martingale inequalities. Convergence properties of discrete time martingales. Introduction to continuous time martingales.
Suggested readings and bibliography
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Textbook:
- Çınlar, E., "Probability and Stochastics", Springer, 2011.
Further suggested books:
- Williams, D., "Probability with Martingales", Cambridge University Press, 2001;
- Shiryaev, A.N., "Probability", Springer, 1996;
- Billingsey, P., "Probability and Measure", Wiley-Interscience, 1995;
- Feller, W. "Introduction to Probability Theory and Applications", 2 Volumes, Wiley, 2008;
- Varadhan, S.R.S., "Probability Theory", AMS, 2001;
- Jacod, J., Protter, P., "Probability Essentials", Springer, 2004.
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Class schedule
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