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 Muhammad El-Taha - University of Southern Maine
Topics: Data Analysis; Probability; Random Variables and Discrete Distributions; Continuous Probability Distributions; Sampling Distributions; Point and Interval Estimation; Large Sample Estimation; Large-Sample Tests of Hypothesis; etc.
by Christophe Garban, Jeffrey E. Steif - arXiv
The goal of this set of lectures is to combine two seemingly unrelated topics: (1) The study of Boolean functions, a field particularly active in computer science; (2) Some models in statistical physics, mostly percolation.
by Matthias Vallentin
The cookbook contains a succinct representation of various topics in probability theory and statistics. It provides a comprehensive reference reduced to the mathematical essence, rather than aiming for elaborate explanations.
by Terence Tao
This is a textbook for a graduate course on random matrix theory, inspired by recent developments in the subject. This text focuses on foundational topics in random matrix theory upon which the most recent work has been based.