Introduction to ProbabilityAmerican Mathematical Soc., 1997 - 510 páginas This text is designed for an introductory probability course at the university level for undergraduates in mathematics, the physical and social sciences, engineering, and computer science. It presents a thorough treatment of probability ideas and techniques necessary for a firm understanding of the subject. |
Índice
Discrete Probability Distributions | 1 |
Combinatorics | 34 |
2 | 75 |
Conditional Probability | 149 |
Distributions and Densities | 183 |
183 | 256 |
Expected Value and Variance | 267 |
Sums of Random Variables | 285 |
Law of Large Numbers | 315 |
Central Limit Theorem | 333 |
Generating Functions | 371 |
Markov Chains | 429 |
Random Walks | 481 |
Appendices | 499 |
| 508 | |
Otras ediciones - Ver todo
Introduction to Probability Charles Miller Grinstead,James Laurie Snell Vista previa restringida - 2012 |
Introduction to Probability David F. Anderson,Timo Seppäläinen,Benedek Valkó Vista previa restringida - 2017 |
Introduction to Probability David F. Anderson,Timo Seppäläinen,Benedek Valkó Vista previa restringida - 2017 |
Términos y frases comunes
approximately assign assume average balls Bernoulli trials binomial distribution calculate called cards Central Limit Theorem Chebyshev's Inequality choose chosen at random coin is tossed consider continuous random variable cumulative distribution function deck defined denote density function dice discrete random variables dollars equal equation ergodic chain estimate event Example Exercise expected number expected value experiment exponential density Figure Find the probability finite formula function f(x fx(x given independent random variables independent trials process integers interval Large Numbers Law of Large Markov chain Mathematics mean normal density normally distributed number of heads obtain occurs offspring pair Pascal percent permutation play player Poisson distribution possible outcomes probability vector problem proof queue random walk real number rolls sample space Show simulation standard normal subset Suppose Table transition matrix variance Write a program