Introduction to Probability with Mathematica

Introduction to Probability with Mathematica PDF Author: Kevin J. Hastings
Publisher: CRC Press
ISBN: 1420079409
Category : Mathematics
Languages : en
Pages : 467

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Book Description
Updated to conform to Mathematica® 7.0, Introduction to Probability with Mathematica®, 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.

Introduction to Probability

Introduction to Probability PDF Author: David F. Anderson
Publisher: Cambridge University Press
ISBN: 110824498X
Category : Mathematics
Languages : en
Pages : 447

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Book Description
This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.

Introduction To Probability, An: With Mathematica®

Introduction To Probability, An: With Mathematica® PDF Author: Edward P C Kao
Publisher: World Scientific
ISBN: 9811245452
Category : Mathematics
Languages : en
Pages : 391

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Book Description
The main objective of this text is to facilitate a student's smooth learning transition from a course on probability to its applications in various areas. To achieve this goal, students are encouraged to experiment numerically with problems requiring computer solutions.

Introduction to Probability

Introduction to Probability PDF Author: Narayanaswamy Balakrishnan
Publisher: John Wiley & Sons
ISBN: 1118548558
Category : Mathematics
Languages : en
Pages : 548

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Book Description
INTRODUCTION TO PROBABILITY Discover practical models and real-world applications of multivariate models useful in engineering, business, and related disciplines In Introduction to Probability: Multivariate Models and Applications, a team of distinguished researchers delivers a comprehensive exploration of the concepts, methods, and results in multivariate distributions and models. Intended for use in a second course in probability, the material is largely self-contained, with some knowledge of basic probability theory and univariate distributions as the only prerequisite. This textbook is intended as the sequel to Introduction to Probability: Models and Applications. Each chapter begins with a brief historical account of some of the pioneers in probability who made significant contributions to the field. It goes on to describe and explain a critical concept or method in multivariate models and closes with two collections of exercises designed to test basic and advanced understanding of the theory. A wide range of topics are covered, including joint distributions for two or more random variables, independence of two or more variables, transformations of variables, covariance and correlation, a presentation of the most important multivariate distributions, generating functions and limit theorems. This important text: Includes classroom-tested problems and solutions to probability exercises Highlights real-world exercises designed to make clear the concepts presented Uses Mathematica software to illustrate the text’s computer exercises Features applications representing worldwide situations and processes Offers two types of self-assessment exercises at the end of each chapter, so that students may review the material in that chapter and monitor their progress Perfect for students majoring in statistics, engineering, business, psychology, operations research and mathematics taking a second course in probability, Introduction to Probability: Multivariate Models and Applications is also an indispensable resource for anyone who is required to use multivariate distributions to model the uncertainty associated with random phenomena.

Introduction to Probability

Introduction to Probability PDF Author: Dimitri Bertsekas
Publisher: Athena Scientific
ISBN: 188652923X
Category : Mathematics
Languages : en
Pages : 544

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Book Description
An intuitive, yet precise introduction to probability theory, stochastic processes, statistical inference, and probabilistic models used in science, engineering, economics, and related fields. This is the currently used textbook for an introductory probability course at the Massachusetts Institute of Technology, attended by a large number of undergraduate and graduate students, and for a leading online class on the subject. The book covers the fundamentals of probability theory (probabilistic models, discrete and continuous random variables, multiple random variables, and limit theorems), which are typically part of a first course on the subject. It also contains a number of more advanced topics, including transforms, sums of random variables, a fairly detailed introduction to Bernoulli, Poisson, and Markov processes, Bayesian inference, and an introduction to classical statistics. The book strikes a balance between simplicity in exposition and sophistication in analytical reasoning. Some of the more mathematically rigorous analysis is explained intuitively in the main text, and then developed in detail (at the level of advanced calculus) in the numerous solved theoretical problems.

A Natural Introduction to Probability Theory

A Natural Introduction to Probability Theory PDF Author: R. Meester
Publisher: Springer Science & Business Media
ISBN: 3764387246
Category : Mathematics
Languages : en
Pages : 201

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Book Description
Compactly written, but nevertheless very readable, appealing to intuition, this introduction to probability theory is an excellent textbook for a one-semester course for undergraduates in any direction that uses probabilistic ideas. Technical machinery is only introduced when necessary. The route is rigorous but does not use measure theory. The text is illustrated with many original and surprising examples and problems taken from classical applications like gambling, geometry or graph theory, as well as from applications in biology, medicine, social sciences, sports, and coding theory. Only first-year calculus is required.

Mathematica Laboratories for Mathematical Statistics

Mathematica Laboratories for Mathematical Statistics PDF Author: Jenny A. Baglivo
Publisher: SIAM
ISBN: 0898715660
Category : Mathematics
Languages : en
Pages : 273

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Book Description
CD-ROM contains text, data, computations, and graphics.

Mathematical Statistics with Mathematica

Mathematical Statistics with Mathematica PDF Author: Colin Rose
Publisher: Springer
ISBN: 9780387952345
Category : Business & Economics
Languages : en
Pages : 508

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Book Description
This text and software package presents a unified approach for doing mathematical statistics with Mathematica. The mathStatica software empowers the student with the ability to solve difficult problems. The professional statistician should be able to tackle tricky multivariate distributions, generating functions, inversion theorems, symbolic maximum likelihood estimation, unbiased estimation, and the checking and correcting of textbook formulae. This is the ideal companion for researchers and students in statistics, econometrics, engineering, physics, psychometrics, economics, finance, biometrics, and the social sciences. The mathStatica CD-ROM includes: mathStatica - the applications pack for mathematical statistics, custom Mathematica palettes, live interactive book that is identical to the printed text, online help, and a trial version of Mathematica 4.0.

Introduction to Probability

Introduction to Probability PDF Author: George G. Roussas
Publisher: Academic Press
ISBN: 0128001984
Category : Mathematics
Languages : en
Pages : 547

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Book Description
Introduction to Probability, Second Edition, discusses probability theory in a mathematically rigorous, yet accessible way. This one-semester basic probability textbook explains important concepts of probability while providing useful exercises and examples of real world applications for students to consider. This edition demonstrates the applicability of probability to many human activities with examples and illustrations. After introducing fundamental probability concepts, the book proceeds to topics including conditional probability and independence; numerical characteristics of a random variable; special distributions; joint probability density function of two random variables and related quantities; joint moment generating function, covariance and correlation coefficient of two random variables; transformation of random variables; the Weak Law of Large Numbers; the Central Limit Theorem; and statistical inference. Each section provides relevant proofs, followed by exercises and useful hints. Answers to even-numbered exercises are given and detailed answers to all exercises are available to instructors on the book companion site. This book will be of interest to upper level undergraduate students and graduate level students in statistics, mathematics, engineering, computer science, operations research, actuarial science, biological sciences, economics, physics, and some of the social sciences. - Demonstrates the applicability of probability to many human activities with examples and illustrations - Discusses probability theory in a mathematically rigorous, yet accessible way - Each section provides relevant proofs, and is followed by exercises and useful hints - Answers to even-numbered exercises are provided and detailed answers to all exercises are available to instructors on the book companion site

The Student's Introduction to MATHEMATICA ®

The Student's Introduction to MATHEMATICA ® PDF Author: Bruce F. Torrence
Publisher: Cambridge University Press
ISBN: 1139473735
Category : Computers
Languages : en
Pages : 484

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Book Description
The unique feature of this compact student's introduction is that it presents concepts in an order that closely follows a standard mathematics curriculum, rather than structure the book along features of the software. As a result, the book provides a brief introduction to those aspects of the Mathematica software program most useful to students. The second edition of this well loved book is completely rewritten for Mathematica 6 including coverage of the new dynamic interface elements, several hundred exercises and a new chapter on programming. This book can be used in a variety of courses, from precalculus to linear algebra. Used as a supplementary text it will aid in bridging the gap between the mathematics in the course and Mathematica. In addition to its course use, this book will serve as an excellent tutorial for those wishing to learn Mathematica and brush up on their mathematics at the same time.