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 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.
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
The 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
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.