Introduction to Probability with Mathematica
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Introduction to Probability with Mathematica

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Updated to conform to Mathematica (R) 7.0, Introduction to Probability with Mathematica (R), Second Edition continues to show students how to easily create simulations from templates and solve problems using Mathematica. It provides a real understanding of probabilistic modeling and the analysis of data and encourages the application of these ideas to practical problems. The accompanying CD-ROM offers instructors the option of creating class notes, demonstrations, and projects.


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 CD-ROM (Go to Downloads/Updates tab for link to CD files.)








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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Product details

  • Hardback | 465 pages
  • 159 x 235 x 30.48mm | 839g
  • Chapman & Hall/CRC
  • Boca Raton, FL, United States
  • English
  • New edition
  • 2nd New edition
  • 125 Illustrations, black and white
  • 1420079387
  • 9781420079388
  • 2,024,641

Table of contents

Discrete Probability


The Cast of Characters


Properties of Probability


Simulation


Random Sampling


Conditional Probability


Independence


Discrete Distributions


Discrete Random Variables, Distributions, and Expectations


Bernoulli and Binomial Random Variables


Geometric and Negative Binomial Random Variables


Poisson Distribution


Joint, Marginal, and Conditional Distributions


More on Expectation


Continuous Probability


From the Finite to the (Very) Infinite


Continuous Random Variables and Distributions


Continuous Expectation


Continuous Distributions


The Normal Distribution


Bivariate Normal Distribution


New Random Variables from Old


Order Statistics


Gamma Distributions


Chi-Square, Student's t, and F-Distributions


Transformations of Normal Random Variables


Asymptotic Theory


Strong and Weak Laws of Large Numbers


Central Limit Theorem


Stochastic Processes and Applications


Markov Chains


Poisson Processes


Queues


Brownian Motion


Financial Mathematics


Appendix


Introduction to Mathematica


Glossary of Mathematica Commands for Probability


Short Answers to Selected Exercises


References


Index
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Review quote

If you own the first edition, you will be very pleased with the second edition. It is more complete, better organized, and even more well-presented. If you don't own the first edition, and are looking for an effective tool for conveying probabilistic concepts, Hastings' book should certainly be one you consider.
-Jane L. Harvill, The American Statistician, November 2011


Introduction to Probability with Mathematica adds computational exercises to the traditional undergraduate probability curriculum without cutting out theory. ... a good textbook for a class with a strong emphasis on hands-on experience with probability. ... One interesting feature of the book is that each set of exercises includes a few problems taken from actuarial exams. No doubt this will comfort students who are taking a probability course in hopes that it will prepare them for an actuarial exam. Another interesting feature is the discussion of the Central Limit Theorem. The book goes into an interesting discussion of the history of the theorem ... .
-MAA Reviews, December 2009
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About Kevin J. Hastings

Kevin J. Hastings is a professor of mathematics at Knox College in Galesburg, Illinois.
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