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Probability Theory 1 Lecture Notes
The contents include: Introduction, Preliminary Results, Distributions, Random Variables, Expectation, Independence, Weak Law of Large Numbers, Borel-Cantelli Lemmas, Strong Law of Large Numbers, Random Series, Weak Convergence, Characteristic Functions, Central Limit Theorems, Poisson Convergence, Stein's Method, Random Walk Preliminaries, Stopping Times, Recurrence, Path Properties, Law of The Iterated Logarithm.
Author(s): John Pike
123 Pages
Lecture Notes for Introductory Probability
The contents include: Combinatorics, Axioms of Probability, Conditional Probability and Independence, Discrete Random Variables, Continuous Random Variables, Joint Distributions and Independence, More on Expectation and Limit Theorems, Convergence in probability, Moment generating functions, Computing probabilities and expectations by conditioning, Markov Chains: Introduction, Markov Chains: Classification of States, Branching processes, Markov Chains: Limiting Probabilities, Markov Chains: Reversibility, Three Application, Poisson Process.
Author(s): Janko Gravner, Mathematics Department, University of California
218 Pages
Theory of Probability by Prof. Scott Sheffield
This note covers topics such as sums of independent random variables, central limit phenomena, infinitely divisible laws, Levy processes, Brownian motion, conditioning, and martingales.
Author(s): Prof. Scott Sheffield
NA Pages
Probability Theory and Statistics Lecture notes
The aim of the notes is to combine the mathematical and theoretical underpinning of statistics and statistical data analysis with computational methodology and practical applications. Topics covered includes: Notion of probabilities, Probability Theory, Statistical models and inference, Mean and Variance, Sets, Combinatorics, Limits and infinite sums, Integration.
Author(s): Niels Richard Hansen
294 Pages
Introduction to Probability Theory and Statistics
This note covers the following topics: Probability, Random variables, Random Vectors, Expected Values, The precision of the arithmetic mean, Introduction to Statistical Hypothesis Testing, Introduction to Classic Statistical Tests, Intro to Experimental Design, Experiments with 2 groups, Factorial Experiments, Confidence Intervals.
Author(s): Javier R. Movellan
127 Pages
These notes are intended to give a solid introduction to Probability Theory with a reasonable level of mathematical rigor. Topics covered includes: Elementary probability, Discrete-time finite state Markov chains, Existence of Markov Chains, Discrete-time Markov chains with countable state space, Probability triples, Limit Theorems for stochastic sequences, Moment Generating Function, The Central Limit Theorem, Measure Theory and Applications.
Author(s): Christopher King
124 Pages
Probability and Stochastic Processes
This book covers the following topics: Basic Concepts of Probability Theory, Random Variables, Multiple Random Variables, Vector Random Variables, Sums of Random Variables and Long-Term Averages, Random Processes, Analysis and Processing of Random Signals, Markov Chains, Introduction to Queueing Theory and Elements of a Queueing System.
Author(s): Dongyu Qiu
NA Pages
Markov Random Fields and Their Applications
This 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.
Author(s): Ross Kindermann and J. Laurie Snell
147 Pages
This note covers the following topics related to Probability: Kolmogorov’s axiomatization, Frequentism, Classical interpretation, Logical probability and Subjectivism.
Author(s): Branden Fitelson, Alan Hajek, and Ned Hall
30 Pages
A quick refresher for Counting techniques and Probability
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Author(s): NA
NA Pages
Introduction to probability and random processes
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NA Pages
Introduction to Probability pdf
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NA Pages
Lectures on Stochastic Analysis
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Markov Chains and Stochastic Stability
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Lecture Notes on Probability Theory (Mrters P ps)
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NA Pages
Lecture Notes on Probability Theory and Random Processes (Walrand J pdf)
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