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
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.
This
note covers topics such as sums of independent random variables, central limit
phenomena, infinitely divisible laws, Levy processes, Brownian motion,
conditioning, and martingales.
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.
This book explains
the following topics: Probability spaces, Random variables, Independence,
Expectation, Convergence of sequences of random variables.
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.
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
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.
This 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.