Introduction to Probability

By Grinstead, Charles M.

Book Id: WPLBN0000660081
Format Type: PDF eBook:
File Size: 0.1 MB
Reproduction Date: 2005

Title:	Introduction to Probability
Author:	Grinstead, Charles M.
Volume:
Language:	English
Subject:	Science., Mathematics, Logic
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Citation APA MLA Chicago M. Grinstea, B. C. (n.d.). Introduction to Probability. Retrieved from http://gutenberg.cc/

Description
Mathematics document containing theorems and formulas.

Excerpt
Excerpt: Probability theory began in seventeenth century France when the two great French mathematicians, Blaise Pascal and Pierre de Fermat, corresponded over two problems from games of chance. Problems like those Pascal and Fermat solved continued to influence such early researchers as Huygens, Bernoulli, and DeMoivre in establishing a mathematical theory of probability. Today, probability theory is a well established branch of mathematics that finds applications in every area of scholarly activity from music to physics, and in daily experience from weather prediction to predicting the risks of new medical treatments.

Table of Contents
Contents 1 Discrete Probability Distributions 1 1.1 Simulation of Discrete Probabilities . . . . . . . . . . . . . . . . . . . 1 1.2 Discrete Probability Distributions . . . . . . . . . . . . . . . . . . . . 18 2 Continuous Probability Densities 41 2.1 Simulation of Continuous Probabilities . . . . . . . . . . . . . . . . . 41 2.2 Continuous Density Functions . . . . . . . . . . . . . . . . . . . . . . 55 3 Combinatorics 75 3.1 Permutations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 3.2 Combinations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 3.3 Card Shuýing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 4 Conditional Probability 133 4.1 Discrete Conditional Probability . . . . . . . . . . . . . . . . . . . . 133 4.2 Continuous Conditional Probability . . . . . . . . . . . . . . . . . . . 162 4.3 Paradoxes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 5 Distributions and Densities 183 5.1 Important Distributions . . . . . . . . . . . . . . . . . . . . . . . . . 183 5.2 Important Densities . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 6 Expected Value and Variance 225 6.1 Expected Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 6.2 Variance of Discrete Random Variables . . . . . . . . . . . . . . . . . 257 6.3 Continuous Random Variables . . . . . . . . . . . . . . . . . . . . . . 268 7 Sums of Random Variables 285 7.1 Sums of Discrete Random Variables . . . . . . . . . . . . . . . . . . 285 7.2 Sums of Continuous Random Variables . . . . . . . . . . . . . . . . . 291 8 Law of Large Numbers 305 8.1 Discrete Random Variables . . . . . . . . . . . . . . . . . . . . . . . 305 8.2 Continuous Random Variables . . . . . . . . . . . . . . . . . . . . . . 316