Probability & Statistical Inference · Probability Theory

Probability inequalities and complementary concepts

Public introduction · full guide in Eikos

Introduction

What this guide covers

A comprehensive tour of the fundamental tools for delimiting the tail of distributions, analyzing the convergence of random variables, and founding modern mathematical statistics.

Overview

Topics covered

  • Introduction
  • Inequalities and Concentration of Measurement
  • Introduction and Measurement Concentration Framework
  • The Concentration Phenomenon
  • Theoretical and Practical Importance
  • Markov Inequality

Related concepts

Main connections

  • Calculus & differentiation
  • Variance & standard deviation
  • Mathematical expectation & moments
  • Mean & expected value
  • Conditional probability & independence
  • Chi-squared tests & goodness of fit

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

fSn(s)=(fX1*fX2*⋯*fXn)(s)
View LaTeX sourcef_{S_n}(s) = (f_{X_1} * f_{X_2} * \cdots * f_{X_n})(s)