Essentials of Probability Theory

Mircea Grigoriu ()
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Mircea Grigoriu: Cornell University

Chapter Chapter 2 in Stochastic Systems, 2012, pp 9-57 from Springer

Abstract: Abstract Essentials of probability theory are reviewed and illustrated by examples. The review covers probability spaces, properties of probability measure, measurable functions and random elements, independence for $$\sigma$$ -fields, events, and random elements, expectation operator, Fubini’s theorem, convergence concepts, Radon–Nikodym derivative, distribution and density functions, characteristic function, conditional expectation, discrete time martingales, and direct and improved Monte Carlo simulation.

Keywords: Probability Measure; Probability Space; Conditional Expectation; Sample Space; Random Element (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-1-4471-2327-9_2

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DOI: 10.1007/978-1-4471-2327-9_2

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