Basic Probability Theory
by Robert B. Ash
Publisher: Dover Publications 2008
Number of pages: 352
This introductory text surveys random variables, conditional probability and expectation, characteristic functions, infinite sequences of random variables, Markov chains, and an introduction to statistics. Geared toward advanced undergraduates and graduate students. The text does not require measure theory, but underlying measure-theoretic ideas are sketched.
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by Pawel J. Szablowski - arXiv
We formulate conditions for convergence of Laws of Large Numbers and show its links with of parts mathematical analysis such as summation theory, convergence of orthogonal series. We present also various applications of Law of Large Numbers.
by Marcel B. Finan - Arkansas Tech University
This manuscript will help students prepare for the Probability Exam, the examination administered by the Society of Actuaries. This examination tests a student's knowledge of the fundamental probability tools for quantitatively assessing risk.
by E. T. Jaynes - Cambridge University Press
The book is addressed to readers familiar with applied mathematics at the advanced undergraduate level. The text is concerned with probability theory and all of its mathematics, but now viewed in a wider context than that of the standard textbooks.
by Alexei Borodin, Vadim Gorin - arXiv
Topics include integrable models of random growth, determinantal point processes, Schur processes and Markov dynamics on them, Macdonald processes and their application to asymptotics of directed polymers in random media.