Our search has the following Google-type functionality:

If you use '+' at the start of a word, that word will be present in the search results.

*eg. Harry +Potter*

*Search results will contain 'Potter'.*

If you use '-' at the start of a word, that word will be absent in the search results.

*eg. Harry -Potter*

*Search results will not contain 'Potter'.*

If you use 'AND' between 2 words, then both those words will be present in the search results.

*eg. Harry AND Potter*

*Search results will contain both 'Harry' and 'Potter'.*

NOTE: AND will only work with single words not phrases.

If you use 'OR' between 2 single words, then either or both of those words will be present in the search results.

*eg. 'Harry OR Potter'*

*Search results will contain just 'Harry', or just 'Potter', or both 'Harry' and 'Potter'.*

NOTE: OR will only work with single words not phrases.

If you use 'NOT' before a word, that word will be absent in the search results. (This is the same as using the minus symbol).

*eg. 'Harry NOT Potter'*

*Search results will not contain 'Potter'.*

NOTE: NOT will only work with single words not phrases.

If you use double quotation marks around words, those words will be present in that order.

*eg. "Harry Potter"*

*Search results will contain 'Harry Potter', but not 'Potter Harry'.*

NOTE: "" cannot be combined with AND, OR & NOT searches.

If you use '*' in a word, it performs a wildcard search, as it signifies any number of characters. (Searches cannot start with a wildcard).

*eg. 'Pot*er'*

*Search results will contain words starting with 'Pot' and ending in 'er', such as 'Potter'.*

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 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.

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

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

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