Lecture notes Probability Theory and StatisticsJorgen LarsenPDF  225 Pages  EnglishThe present
set of lecture notes is directed at students who have to do a certain amount of
probability theory and statistics as part of their general mathematics
education, and accordingly it is directed neither at students specializing in
probability or statistics nor at students in need of statistics as an ancillary
subject.

Markov Random Fields and Their ApplicationsRoss Kindermann and J. Laurie SnellOnline  147 Pages  EnglishThis book presents the basic
ideas of the subject and its application to a wider audience. Topics covered
includes: The Ising model, Markov fields on graphs, Finite lattices, Dynamic
models, The tree model and Additional applications.

Stochastic Analysis NotesIvan
F WildePDF  103 Pages  EnglishThis note covers the following topics: Conditional expectation ,
Martingales , Stochastic integrationinformally , Wiener process and Ito’s
Formula.

Probabilistic ThinkingRichard
JeffreyOnline  NA Pages  EnglishThis note covers the following topics related to Probability: Laws Of
Probability, Methodology, Expectation, Decision, Probabilism and Induction.

Probability papersBranden
Fitelson, Alan Hajek, and Ned HallPDF  30 Pages  EnglishThis note covers the following topics related
to Probability: Kolmogorov’s axiomatization, Frequentism, Classical
interpretation, Logical probability and Subjectivism.

Probability and Stochastic Processes with ApplicationsOliver
KnillPDF  382 Pages  EnglishThis text assumes no prerequisites in probability, a basic exposure to
calculus and linear algebra is necessary. Some real analysis as well as some
background in topology and functional analysis can be helpful. This note covers
the following topics: Limit theorems, Probability spaces, random variables,
independence, Markov operators, Discrete Stochastic Processes, Continuous
Stochastic Processes, Random Jacobi matrices, Symmetric Diophantine Equations
and Vlasov dynamics.

Lecture Notes on Probability Theory and Random ProcessesJean
WalrandPDF  302 Pages  EnglishThe goal to to help the student figure out the meaning of various
concepts in Probability Theory and to illustrate them with examples. Topics
covered includes: Modelling Uncertainty, Probability Space, Conditional
Probability and Independence, Random Variable, Conditional Expectation, Gaussian
Random Variables, Limits of Random Variables, Filtering Noise and Markov Chains

Probability Theory The Logic of ScienceE. T. JaynesPDF  95 Pages  EnglishThis book is addressed to readers who
are already familiar with applied mathematics at the advanced undergraduate level or preferably higher. Topics covered
includes: Plausible Reasoning, Quantitative Rules, Elementary Sampling Theory,
Elementary Hypothesis Testing, Queer Uses For Probability Theory, Elementary
Parameter Estimation, Central, Gaussian Or Normal Distribution.

Introduction to Probability clark eduProf.
D. JoyceOnline  NA Pages  EnglishThis note provides an introduction to probability theory and
mathematical statistics that emphasizes the probabilistic foundations required
to understand probability models and statistical methods. Topics covered
includes the probability axioms, basic combinatorics, discrete and continuous
random variables, probability distributions, mathematical expectation, common
families of probability distributions and the central limit theorem.

A Compendium of Common Probability DistributionsMichael
P. McLaughlinPDF  136 Pages  EnglishThis document describes the distributions available in Regress+
(v2.7).This Compendium supplies the formulas and parametrization as utilized in
the software plus additional formulas, notes, etc.

Probability, Random Processes, and Ergodic Properties 
Grinstead and Snells Introduction to Probability 
Notes on Probability 
A quick refresher for Counting techniques and Probability 
MEASURE INTEGRATION PROBABILITY 
Beyond PROBABILITY 
Introduction to probability and random processes 
Introduction to Probability pdf 
Introduction to Probability 
The Four Color Theorem 
Reversible Markov Chains and Random Walks on Graphs 
Undergraduate probability 
PDE from a probability point of view 
Lecture notes for the Cornell Summer School in Probability 2007 
Stochastic Calculus 
Lectures on Stochastic Analysis 
Markov Chains and Stochastic Stability 
Stochastic Analysis Notes 
Introduction to Statistical Signal Processing Gray R.M. and Davisson L.D 
Lecture Notes on Probability Theory (Mrters P ps) 
Lecture Notes on Probability Theory and Random Processes (Walrand J pdf) 
Undergraduate Probability (Bass R.F pdf) 
Introduction to Probability (Grinstead C.M. and Snell J.L) 