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 Prasanna Sahoo - University of Louisville
This book is an introduction to probability and mathematical statistics intended for students already having some elementary mathematical background. It is intended for a one-year junior or senior level undergraduate or beginning graduate course.
by R. A. Bailey - Cambridge University Press
This book develops a coherent framework for thinking about factors that affect experiments and their relationships, including the use of Hasse diagrams. The book is ideal for advanced undergraduate and beginning graduate courses.
by David Aldous, James Allen Fill - University of California, Berkeley
From the table of contents: General Markov Chains; Reversible Markov Chains; Hitting and Convergence Time, and Flow Rate, Parameters for Reversible Markov Chains; Special Graphs and Trees; Cover Times; Symmetric Graphs and Chains; etc.
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.