Introduction to Probability Theory and Statistics for Linguistics
by Marcus Kracht
Publisher: UCLA 2005
Number of pages: 137
Contents: Basic Probability Theory (Probability Spaces, Conditional Probability, Random Variables, Expected Word Length, Limit Theorems); Elements of Statistics (Estimators, Tests, Distributions, Correlation and Covariance, Linear Regression, Markov Chains); Probabilistic Linguistics (Probabilistic Regular Languages and Hidden Markov Models).
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by Thomas G. Kurtz - University of Wisconsin
Covered topics: stochastic integrals with respect to general semimartingales, stochastic differential equations based on these integrals, integration with respect to Poisson measures, stochastic differential equations for general Markov processes.
by O. Melchert - arXiv
In these lecture notes, a selection of frequently required statistical tools will be introduced and illustrated. They allow to post-process data that stem from, e.g., large-scale numerical simulations (aka sequence of random experiments).
by D. Koutsoyiannis - National Technical University of Athens
Contents: The utility of probability; Basic concepts of probability; Elementary statistical concepts; Special concepts of probability theory in geophysical applications; Typical univariate statistical analysis in geophysical processes; etc.
by Luc Devroye - Springer
The book on small field on the crossroads of statistics, operations research and computer science. The applications of random number generators are wide and varied. The study of non-uniform random variates is precisely the subject area of the book.