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The Four Color Theorem

The Four Color Theorem

The Four Color Theorem

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Probability Theory 1 Lecture Notes

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.

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Probability Theory Lecture Notes by Phanuel Mariano

Probability Theory Lecture Notes by Phanuel Mariano

The contents include: Combinatorics, Axioms of Probability, Independence, Conditional Probability and Independence, Random Variables, Some Discrete Distributions, Continuous Random Variable, Normal Distributions, Normal approximations to the binomial, Some continuous distributions, Multivariate distributions, Expectations, Moment generating functions, Limit Laws.

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Lecture Notes for Introductory Probability

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.

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Probability Theory and Statistics Lecture notes

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.

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Introduction to Probability Theory and Statistics

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.

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Notes on Probability Theory and Statistics

Notes on Probability Theory and Statistics

This note explains the following topics: Probability Theory, Random Variables, Distribution Functions, And Densities, Expectations And Moments Of Random Variables, Parametric Univariate Distributions, Sampling Theory, Point And Interval Estimation, Hypothesis Testing, Statistical Inference, Asymptotic Theory, Likelihood Function, Neyman or Ratio of the Likelihoods Tests.

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Markov Random Fields and Their Applications

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.

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Probability Theory The Logic of Science

Probability Theory The Logic of Science

This 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.

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Introduction to Probability clark edu

Introduction to Probability clark edu

This 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.

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A Compendium of Common Probability Distributions

A Compendium of Common Probability Distributions

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A quick refresher for Counting techniques and Probability

A quick refresher for Counting techniques and Probability

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Introduction to probability and random processes

Introduction to probability and random processes

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The Four Color Theorem

The Four Color Theorem

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Lectures on Stochastic Analysis

Lectures on Stochastic Analysis

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Stochastic Analysis Notes

Stochastic Analysis Notes

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Introduction to Statistical Signal Processing Gray R.M. and Davisson L.D

Introduction to Statistical Signal Processing Gray R.M. and Davisson L.D

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