Introduction to ProbabilityAmerican Mathematical Soc., 30 de out. de 2012 - 510 páginas This text is designed for an introductory probability course at the university level for sophomores, juniors, and seniors in mathematics, physical and social sciences, engineering, and computer science. It presents a thorough treatment of ideas and techniques necessary for a firm understanding of the subject. |
Conteúdo
Discrete Probability Distributions | 1 |
Continuous Probability Densities | 41 |
Combinatorics | 75 |
Conditional Probability | 133 |
Distributions and Densities | 183 |
Expected Value and Variance | 225 |
Sums of Random Variables | 285 |
Law of Large Numbers | 305 |
Central Limit Theorem | 325 |
Generating Functions | 365 |
Markov Chains | 405 |
Random Walks | 471 |
Appendices | 499 |
Outras edições - Ver todos
Introduction to Probability David F. Anderson,Timo Seppäläinen,Benedek Valkó Visualização parcial - 2017 |
Introduction to Probability David F. Anderson,Timo Seppäläinen,Benedek Valkó Visualização parcial - 2017 |
Termos e frases comuns
approximately assign assume average balls bar graph Bernoulli trials binomial distribution branching process calculate called cards Central Limit Theorem choose chosen at random coin is tossed consider continuous random variable cumulative distribution function deck defined definition denote density function dice discrete random variables distribution with parameter dollars equal equation ergodic chain estimate event Example Exercise expected number expected value experiment exponential density Figure find Find the probability finite first formula function f gambler given independent random variables independent trials process infinite integers interval Large Numbers Law of Large Let X1 Markov chain Mathematics mean normally distributed number of heads obtain occurs offspring pair Pascal percent permutation play player Poisson distribution possible outcomes probability vector problem proof queue random numbers random walk real number rolls sample space Show shown simulation subset Suppose Table transition matrix Write a program