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Author: L. Z. Rumshiskii Publisher: Elsevier ISBN: 1483136000 Category : Mathematics Languages : en Pages : 173
Book Description
Elements of Probability Theory focuses on the basic ideas and methods of the theory of probability. The book first discusses events and probabilities, including the classical meaning of probability, fundamental properties of probabilities, and the primary rule for the multiplication of probabilities. The text also touches on random variables and probability distributions. Topics include discrete and random variables; functions of random variables; and binomial distributions. The selection also discusses the numerical characteristics of probability distributions; limit theorems and estimates of the mean; and the law of large numbers. The text also describes linear correlation, including conditional expectations and their properties, coefficient of correlation, and best linear approximation to the regression function. The book presents tables that show the values of the normal probability integral, Poisson distribution, and values of the normal probability density. The text is a good source of data for readers and students interested in probability theory.
Author: L. Z. Rumshiskii Publisher: Elsevier ISBN: 1483136000 Category : Mathematics Languages : en Pages : 173
Book Description
Elements of Probability Theory focuses on the basic ideas and methods of the theory of probability. The book first discusses events and probabilities, including the classical meaning of probability, fundamental properties of probabilities, and the primary rule for the multiplication of probabilities. The text also touches on random variables and probability distributions. Topics include discrete and random variables; functions of random variables; and binomial distributions. The selection also discusses the numerical characteristics of probability distributions; limit theorems and estimates of the mean; and the law of large numbers. The text also describes linear correlation, including conditional expectations and their properties, coefficient of correlation, and best linear approximation to the regression function. The book presents tables that show the values of the normal probability integral, Poisson distribution, and values of the normal probability density. The text is a good source of data for readers and students interested in probability theory.
Author: Francesca Biagini Publisher: Springer ISBN: 3319072544 Category : Mathematics Languages : en Pages : 246
Book Description
This book provides an introduction to elementary probability and to Bayesian statistics using de Finetti's subjectivist approach. One of the features of this approach is that it does not require the introduction of sample space – a non-intrinsic concept that makes the treatment of elementary probability unnecessarily complicate – but introduces as fundamental the concept of random numbers directly related to their interpretation in applications. Events become a particular case of random numbers and probability a particular case of expectation when it is applied to events. The subjective evaluation of expectation and of conditional expectation is based on an economic choice of an acceptable bet or penalty. The properties of expectation and conditional expectation are derived by applying a coherence criterion that the evaluation has to follow. The book is suitable for all introductory courses in probability and statistics for students in Mathematics, Informatics, Engineering, and Physics.
Author: C. R. Heathcote Publisher: Courier Corporation ISBN: 0486153401 Category : Mathematics Languages : en Pages : 305
Book Description
DIVText deals with basic notions of probablity spaces, random variables, distribution and generating functions, joint distributions and the convergence properties of sequences of random variables. Over 250 exercises with solutions. /div
Author: Nancy Kress Publisher: Macmillan ISBN: 9780765345141 Category : Fiction Languages : en Pages : 372
Book Description
Nancy Kress cemented her reputation in SF with the publication of her multiple-award–winning novella, “Beggars in Spain,” which became the basis for her extremely successful Beggars Trilogy (comprising Beggars in Spain, Beggars and Choosers, and Beggars Ride). And now she brings us Probability Space, the conclusion of the trilogy that began with Probability Moon and then Probability Sun, which is centered on the same world as Kress’s Nebula Award-winning novelette, “Flowers of Aulit Prison.” The Probability Trilogy has already been widely recognized as the next great work by this important SF writer. In Probability Space, humanity’s war with the alien Fallers continues, and it is a war we are losing. Our implacable foes ignore all attempts at communication, and they take no prisoners. Our only hope lies with an unlikely coalition: Major Lyle Kaufman, retired warrior; Marbet Grant, the Sensitive who’s involved with Kaufman; Amanda, a very confused fourteen-year-old girl; and Magdalena, one of the biggest power brokers in all of human space. As the action moves from Earth to Mars to the farthest reaches of known space, with civil unrest back home and alien war in deep space, four humans--armed with little more than an unproven theory--try to enter the Fallers’ home star system. It’s a desperate gamble, and the fate of the entire universe may hang in the balance.
Author: Thomas A. Severini Publisher: Cambridge University Press ISBN: 1139446118 Category : Mathematics Languages : en Pages : 3
Book Description
This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively.
Author: L. Z. Rumshiskii
Author: L. Z. Rumshiskii
Author: Francesca Biagini
Author: Harald Cramér
Author: Harald Cramér
Author: L. Z. Rumshiskii
Author: C. R. Heathcote
Author: Nancy Kress
Author: Harald Cramer
Author: Thomas A. Severini
Author: John Duncan Davies