Introduction to Probability with Mathematica
Autor Kevin J. Hastingsen Limba Engleză Paperback – 19 sep 2019
New to the Second Edition
- Expanded section on Markov chains that includes a study of absorbing chains
- New sections on order statistics, transformations of multivariate normal random variables, and Brownian motion
- More example data of the normal distribution
- More attention on conditional expectation, which has become significant in financial mathematics
- Additional problems from Actuarial Exam P
- New appendix that gives a basic introduction to Mathematica
- New examples, exercises, and data sets, particularly on the bivariate normal distribution
- New visualization and animation features from Mathematica 7.0
- Updated Mathematica notebooks on the downloadable resources.
After covering topics in discrete probability, the text presents a fairly standard treatment of common discrete distributions. It then transitions to continuous probability and continuous distributions, including normal, bivariate normal, gamma, and chi-square distributions. The author goes on to examine the history of probability, the laws of large numbers, and the central limit theorem. The final chapter explores stochastic processes and applications, ideal for students in operations research and finance.
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Specificații
ISBN-13: 9780367385194
ISBN-10: 0367385198
Pagini: 468
Dimensiuni: 156 x 234 x 23 mm
Greutate: 0.45 kg
Ediția:2nd edition
Editura: CRC Press
Colecția Chapman and Hall/CRC
ISBN-10: 0367385198
Pagini: 468
Dimensiuni: 156 x 234 x 23 mm
Greutate: 0.45 kg
Ediția:2nd edition
Editura: CRC Press
Colecția Chapman and Hall/CRC
Public țintă
Academic and Professional Practice & DevelopmentCuprins
Discrete Probability. Discrete Distributions. Continuous Probability. Continuous Distributions. Asymptotic Theory. Stochastic Processes and Applications. Appendix. References. Index.
Notă biografică
Kevin J. Hastings is a professor of mathematics at Knox College in Galesburg, Illinois.
Descriere
Updated to conform to Mathematica® 7.0, this second edition shows how to easily create simulations from templates and solve problems using Mathematica. Along with new sections on order statistics, transformations of multivariate normal random variables, and Brownian motion, this edition offers an expanded section on