Multivariate Calculus and Mathematica: With Applications to Geometry and Physics

Book Description

One of the authors' stated goals for this publication is to "modernize" the course through the integration of Mathematica. Besides introducing students to the multivariable uses of Mathematica, and instructing them on how to use it as a tool in simplifying calculations, they also present intoductions to geometry, mathematical physics, and kinematics, topics of particular interest to engineering and physical science students. In using Mathematica as a tool, the authors take pains not to use it simply to define things as a whole bunch of new "gadgets" streamlined to the taste of the authors, but rather they exploit the tremendous resources built into the program. They also make it clear that Mathematica is not algorithms. At the same time, they clearly see the ways in which Mathematica can make things cleaner, clearer and simpler. The problem sets give students an opportunity to practice their newly learned skills, covering simple calculations with Mathematica, simple plots, a review of one-variable calculus using Mathematica for symbolic differentiation, integration and numberical integration. They also cover the practice of incorporating text and headings into a Mathematica notebook. A DOS-formatted diskette accompanies the printed work, containing both Mathematica 2.2 and 3.0 version notebooks, as well as sample examination problems for students. This supplementary work can be used with any standard multivariable calculus textbook. It is assumed that in most cases students will also have access to an introductory primer for Mathematica.

Customer Reviews:

awful book.......2005-03-30

This is one of the worst technical books I have ever read. It seems like something cobbled together. It teaches very little vector calculus or mathematica.

Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica Support

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Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica Support
P. C. Gregory
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Hardcover

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ASIN: 052184150X

Book Description

Researchers in many branches of science are increasingly coming into contact with Bayesian statistics or Bayesian probability theory. This book provides a clear exposition of the underlying concepts with large numbers of worked examples and problem sets. It also discusses numerical techniques for implementing the Bayesian calculations, including Markov Chain Monte-Carlo integration and linear and nonlinear least-squares analysis seen from a Bayesian perspective.

Download Description

Increasingly, researchers in many branches of science are coming into contact with Bayesian statistics or Bayesian probability theory. By encompassing both inductive and deductive logic, Bayesian analysis can improve model parameter estimates by many orders of magnitude. It provides a simple and unified approach to all data analysis problems, allowing the experimenter to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. This book provides a clear exposition of the underlying concepts with large numbers of worked examples and problem sets. The book also discusses numerical techniques for implementing the Bayesian calculations, including an introduction to Markov Chain Monte-Carlo integration and linear and nonlinear least-squares analysis seen from a Bayesian perspective. In addition, background material is provided in appendices and supporting Mathematica notebooks are available, providing an easy learning route for upper-undergraduates, graduate students, or any serious researcher in physical sciences or engineering.

Introduction to the Mathematics of Operations Research with Mathematica®, Second Edition (Pure and Applied Mathematics)

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Introduction to the Mathematics of Operations Research with Mathematica®, Second Edition (Pure and Applied Mathematics)
Kevin J. Hastings
Manufacturer: Chapman & Hall/CRC
ProductGroup: Book
Binding: Hardcover

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ASIN: 1574446126

Book Description

The breadth of information about operations research and the overwhelming size of previous sources on the subject make it a difficult topic for non-specialists to grasp. Fortunately, Introduction to the Mathematics of Operations Research with Mathematica®, Second Edition delivers a concise analysis that benefits professionals in operations research and related fields in statistics, management, applied mathematics, and finance. The second edition retains the character of the earlier version, while incorporating developments in the sphere of operations research, technology, and mathematics pedagogy. Covering the topics crucial to applied mathematics, it examines graph theory, linear programming, stochastic processes, and dynamic programming. This self-contained text includes an accompanying electronic version and a package of useful commands. The electronic version is in the form of Mathematica notebooks, enabling you to devise, edit, and execute/reexecute commands, increasing your level of comprehension and problem-solving. Mathematica sharpens the impact of this book by allowing you to conveniently carry out graph algorithms, experiment with large powers of adjacency matrices in order to check the path counting theorem and Markov chains, construct feasible regions of linear programming problems, and use the "dictionary" method to solve these problems. You can also create simulators for Markov chains, Poisson processes, and Brownian motions in Mathematica, increasing your understanding of the defining conditions of these processes. Among many other benefits, Mathematica also promotes recursive solutions for problems related to first passage times and absorption probabilities.

Introduction to Probability with Mathematica (Studies in Advanced Mathematics)

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Sample Programs are Available
An excellent book
A creative and refreshing approach...
I was a guinea pig
No software available

Introduction to Probability with Mathematica (Studies in Advanced Mathematics)
Kevin J. Hastings
Manufacturer: Chapman & Hall/CRC
ProductGroup: Book
Binding: Hardcover

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ASIN: 1584881097

Book Description

Newcomers to the world of probability face several potential stumbling blocks. They often struggle with key concepts-sample space, random variable, distribution, and expectation; they must regularly confront integration, infrequently mastered in calculus classes; and they must labor over lengthy, cumbersome calculations. Introduction to Probability with Mathematica is a groundbreaking text that uses a powerful computer algebra system as a pedagogical tool for learning and using probability. Its clever use of simulation to illustrate concepts and motivate important theorems gives it an important and unique place in the library of probability theory. The author smoothly integrates the technology with the traditional approach and subject matter, thereby augmenting rather than overpowering it. This book lives and breathes in the sense that not only can it be read and studied in an armchair, but each section also exists as a fully executable Mathematica® notebook on the CRC Web site. Students will find Introduction to Probability with Mathematica an engaging, accessible, yet challenging way to venture into the fascinating subject of probability.

Customer Reviews:

Sample Programs are Available.......2004-12-30

One reviewer said that the sample programs were not available as promised on the publishers website. That may have been true when that review was written, however, I just checked and the sample programs are now there for download on the publisher's website. In fact, I just downloaded them and they are fully functioning Mathematica notebooks.

An excellent book.......2003-12-12

I purchased this book in desperation while taking a probability class with another textbook, and it has been a lucky find, indeed. The mathematics are limited mostly to basic calculus but provide sufficient rigor to satisfy the interests of mathematically-minded readers. The concepts appeal intuitively to the non-statistician scientist or graduate student as well as the mathematician. This book is easy to read and understand. Mathematica enhances the text and aids the homework, but unlike the reviewer below, I believe this book is valuable even without Mathematica. After reading this book I was able to make sense of the assigned probability text and began to enjoy the course. Introduction to Probability with Mathematica was well worth the investment.

A creative and refreshing approach..........2003-11-05

I considered this book for a course that I thought I was going to teach. The course never got offered but I did discover this neat book in the process. Being a Mathematica fan, I was very happy to see a probability book completely based on Mathematica. In fact, the book itself is a set of Mathematica notebooks, making it very easy for the readers to experiment with the introduced topics. The explanations are clear and are accompanied with neat examples showing real-world uses of probability.

There should be more books like this... Really.

........

I was a guinea pig.......2001-01-09

I was one of the test users of this book at the college where Prof. Hastings teaches. With the use of Mathematica (which is assumed in this book), the book allows one to explore the ideas much more easily. By modifying built in commands, the user can get a better grasp on how specific distributions behave. The commands written for the book are also very helpful. I found the book easy to use and the problems ranged from basic to difficult, but most were intersting (particularly the chapter on simulation). For those with access to Mathematica, this book works seemlessly with the program, making Mathematica a simple to use tool to aid in the understanding of probability rather than get in the way.

No software available.......2000-12-27

The book seems to have good intentions.. but... most of the text uses Mathematica Code that is not available... the promised software on the publishers Website is apparently vaporware.. totally unavailable.. and of course the publishers are "not available"... Without software the book is an expensive waste of time...

Modeling Financial Derivatives With Mathematica (Includes CD-ROM)

Average customer rating:

Excellent Practical Tool for Financial Engineers
A potentially very good book with a very messy presentation.
Highly recommended for researchers in finance
Splendid
Further author comments on reader comments

Modeling Financial Derivatives With Mathematica (Includes CD-ROM)
William T. Shaw
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Hardcover

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ASIN: 052159233X

Book Description

One of the most important tasks in finance is to find good mathematical models for financial products, in particular derivatives. However, the more realistic the model, the more practitioners face still-unsolved problems in rigorous mathematics and econometrics, in addition to serious numerical difficulties. The idea behind this book is to use Mathematica® to provide a wide range of exact benchmark models against which inexact models can be tested and verified. In so doing, the author is able to explain when models and numerical schemes can be relied on, and when they can't. Benchmarking is also applied to Monte Carlo simulations. Mathematica's graphical and animation capabilities are exploited to show how a model's characteristics can be visualized in two and three dimensions. The models described are all available on an accompanying CD that runs on most Windows, Unix and Macintosh platforms; to be able fully to use the software, Mathematica 3 is required, although certain features are usable with Mathematica 2.2. This product will prove of inestimable worth for financial instrument valuation and hedging, checking existing models and for analyzing derivatives; it can be used for professional or training purposes in financial institutions or universities, and in MBA courses.

Customer Reviews:

Excellent Practical Tool for Financial Engineers.......2002-06-07

I found William Shaw's book fascinating when I first bought it back in 1999 and have recently gone back to it for some further insight on some complex problems in finance.
It is a well-structured book that requires a basic understanding of both quantitative finance and Mathematica before you can really get to grips with it BUT having said that the complexity that the author gets to is excellent.
I would recommend this book to anyone in University studying for a Quant-rlated finance Masters or PhD - and anyone practicing in the real world - this should be on your shelf alongisde your copy of Mathematica.

A potentially very good book with a very messy presentation........2001-08-13

My comments are confined to the chapters on trees and finite difference methods, because that was my primary interest in buying the book. I'll say one positive thing about this book -- it does touch on many pitfalls of pricing derivatives with numerical methods such as finite differences and trees.

However my chief complaint is with the way the (very interesting and important) contect is presented -- Shaw simply contents himself with showing pages and pages of mathematica code, which is ugly and annoying to read. He doesn't even use indentations or keyword-highlighting to make the Mathematica code easier to read. What an unbelievable four-letter-word mess! Many mathematical concepts are buried within Mathematica code. A much better book would have resulted if he sat down and presented math as math rather than as Mathematica code. Very disappointing work from a writer who clearly seems to have an in-depth knowledge of finite difference methods.

Highly recommended for researchers in finance.......2001-07-14

It is highly recommended for its broad base of knowledge. People who want to do research in the field of finance must be equipped with this book.

Splendid.......2001-05-01

This is fascinating work, probably Shaw'a best. A real page turner, it keeps a reader glued until the last page. I must reccomend this book very highly, whether you are a serious student of finance or not.

Further author comments on reader comments.......2001-02-21

Some recent comments seem to require response.

1. The Parkville, Aus reader seems to be confused about the use of Monte Carlo simulation. The MC methods use LOG-normal methods, not Normal. Note that one can use several methods for simulating paths of asset prices. I have highlighted 3 approaches (i) fine clockwork paths, (ii) coarse clockwork paths, (iii) "events" or arbitrary time intervals (pp 407-411). Choice (i) should NOT be used for large time intervals or large volatility, as method (i) is based on the differential, and hence, for finite time intervals, approximate, form of the random walk, whereas (ii) and (iii) use the accurate integrated form, and will never give negative asset prices. In fact the book is generally rather clear on the need to avoid negative asset prices, and, in the case of tree models, carefully avoids either negative asset prices or probabilities, unlike most other texts!

Book Description

This book 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 will 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, trail version of Mathematica 4.0. Colin Rose is Director of the Theoretical Research Institute (Sydney). He has published in leading journals on computer algebra systems and their applications to statistics, economics, and finance. Murry Smith is a senior lecturer in the Department of Econometrics and Business Statistics at the University of Sydney. In 1998-99, he was awarded an Alexander von Humboldt Research Fellowship to visit the University of Munich. He publishes in the fields of statistics, econometric theory, and computer algebra systems. WINNER of The MDTech Prize for Best Software Contribution at COMPSTAT 2002!

Customer Reviews:

One for practitioners.......2006-10-15

This book fills a niche nicely. I cheerfully recommend it to applied researchers who, like me, learned their statistics haphazardly in the context of a discipline like economics or biology. The book works rather like a cookbook should, offering up detailed recipes for a great variety of problems, while the software delivers tools which tackle those problems in a no-nonsense style. Would any of this appeal to true, or budding, affionados of mathematical statistics? Hmmm.

As other reviewers have suggested, there is indeed something unfortunate about the marketing of this book. It is not much without the software, and you can't license the full-version of the software without first having bought the book.

But these are really second-order gripes. If you are trying to extend the statistical capabilities of Mathematica at a practical level, the total package amply justifies the price.

Powerful software great for learning and experimenting.......2006-07-14

The bottom line is that this is a very well written book, but more importantly the associated software is *very powerful*. The software is a *symbolic* solver for mathematical statistics, not merely a numerical solver. You will appreciate the great value of this book and software once you understand this difference. Great if you want to learn, experiment and apply mathematical statistics. I highly recommend it.

OK book........2006-03-10

mathStatica, a software bundled with this book, is probably a very good software. I was not very happy with the way the authors and the publisher structured the mathStatica license, particularly with newer and improved versions of Mathematica and the limited use of the software. The Mathematica descriptions were useful with the exercises beneficial.

Modern text.......2006-01-12

This text comes bundled with mathStatica 1.0. The version of the bundled software works fine with Mathematica 4, but not at all with Mathematica 5. Mathematica 5 users need to upgrade to the latest version of the mathStatica software which is mathStatica 1.5 at the time of my writing this. While this costs extra, book owners receive a $70 discount - not too bad given that the book costs a similar amount altogether. The mathStatica software is excellent - I'm not going to review it here - this is a book review, not a software review - suffice to say it won the CompStat Best Software award.

As for the book, this is a modern text with clean modern ideas expressed in a rigorous and clear manner. The CD includes everything as Mathematica notebooks that open chapter by chapter from palettes, live indexing etc - nice.

Much of the material in 'Math Stats with Mma' is similar to Kendall's "Advanced Theory of Stats", and yet despite the material being of an advanced level, the elegance of this text, when combined with Mathematica and the mathStatica software, is that the 'advanced' material becomes 'easy' and manageable, even at an undergrad level, as others have noted. I would not normally comment on other comments, but Mr Dudding's assertion (see comment below) that the level is 'barely undergrad' is just silly, if not confused. Making something that is difficult into something that is easy takes considerable skill and expertise and that is what this text is all about -- whereas any idiot can do the converse: take something simple and make it appear difficult. Dudding seems to want to take a clean modern text on stat computing and clutter it up with formal proofs that already exist in 1001 other texts on math stats - I just don't see how such proofs - usually well-known - belong in ANY book on computational statistics ... and they certainly don't belong here. As appropriate for a text on stat computing, this one gets down to solving your problems, not just repeating the material every other text repeats.

Much to recommend. I'd like to see some MCMC material added. Five stars.

Glorified software pitch.......2005-10-22

Although Mathematica is a very versatile package, the developers at Wolfram have largely ignored statistical applications beyond the very basic. For example, even its basic uniform random generator is rather primitive and users have to recourse to third party solutions available freely on the web. There clearly is a need for development in this area and I purchased this book with much hope.

However, after reading this book, I could not figure out whether this was supposed to teach Mathematical Statistics or Mathematica. In my opinion, it does neither.

The level of mathematical statistics covered is barely up to undergraduate level. There are virtually no proofs and the lack of rigor is often distracting. The intuitive ideas behind some of the basic results are helpful, but there are much better texts already in the market in this regard.

As far Mathematica is concerned, *the entire Mathstatica package is encrypted so you never get to see the code!* You just have to accept it as a black box. This makes the book practically useless for me. Btw, even after purhcasing the book you do not get the entire software package but a limited version of it. They want about $89 more for the full version. Most of the book teaches how to use this package, and barely adds anything beyond the help files. There is virtually nothing new to learn about Mathematica or implementing statistics in Mathematica in this book!

This book by no means an addition to the academic literature. It is more of a software advertisement and that too is rather overpriced for what it achieves.

Economic and Financial Modeling with Mathematica (R)

Average customer rating:

Somewhat dated...but still helpful

Economic and Financial Modeling with Mathematica (R)

Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

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ASIN: 0387978828

Book Description

Mathematica is a computer program (software) for doing symbolic, numeric and graphical analysis of mathematical problems. In the hands of economists, financial analysts and other professionals in econometrics and the quantitative sector of economic and financial modeling, it can be an invaluable tool for modeling and simulation on a large number of issues and problems, besides easily grinding out numbers, doing statistical estimations and rendering graphical plots and visuals. Mathematica enables these individuals to do all of this in a unified environment. This book's main use is that of an applications handbook. Modeling in Economics and Finance with Mathematica is a compilation of contributed papers prepared by experienced, "hands on" users of the Mathematica program. They come from a broad spectrum of Mathematica devotees in the econometric and financial/investment community on both the professional and academic fronts. Each paper provides a set of tools and examples of Mathematica in action. These tools will also be made accessible to users via a DOS-based floppy disk which will contain Mathematica Notebooks and Packages, and be packaged with the book.

Customer Reviews:

Somewhat dated...but still helpful.......2002-01-19

For the reader well-versed in Mathematica and in economic theory, this book gives a fairly good overview of how Mathematica can be used to study mathematical economics and finance. It is also assumed in the articles in the book that the reader has a strong background in mathematics. Since the book was published in 1993, Mathematica has considerably expanded, with many new features that make some of the accompanying code in the book somewhat dated, but the notebooks can still be used beneficially.In addition, economic theory is currently making more use of symbolic programming, and financial analysis has exploded as an area which is now making heavy use of high-performance computing. Although Mathematica cannot compete from a performance standpoint with the needs of financial engineering, it still has an advantage from a didactic standpoint. I did not read all of the articles in the book, so my comments will be limited to the ones that I did.

The article on "Mathematica and Diffusions" is an overview of how to use Mathematica to do stochastic calculus. The Ito calculus is reviewed briefly, and the authors begin with constructing a Weiner process. The Mathematica package they employ and on the disk accompanying the book is not discussed in detail, but is merely used to simulate realizations of the process. Readers who want a more in-depth view will have to go over the code themselves. The authors use the package to generate realizations of Weiner processes that are correlated with each other, and show this correlation via Mathematica graphics. The Black-Scholes formula is derived using the standard self-financing trading strategy and ignoring transaction costs and dividends. The algebraic manipulations are done with Mathematica, and this obscures (a little) the underlying concepts behind the derivation of this important formula. Since data structures in Mathematica are essentially lists, the authors outline the construction of the data structure that could be used to represent a diffusion, namely a list consisting of five terms: the diffusion, Weiner process name, expression for the drift and dispersion, and the initial value. For the reader familiar with OO-programming, accessor functions are used to extract the components of this data structure. This is a nice move by the authors, for it is an example of how Mathematica can be used to emulate OO-programming.

The article "Itovsn3: Doing Stochastic Calculus with Mathematica" is an overview of how to use the Itovsn3 package that is on the disk to implement Ito calculus. It is assumed that the reader has a background in stochastic calculus, since the author does not give a review. However, semimartingales, so important to those working in financial engineering, are discussed and their statistical behavior described using Mathematica. The Ito formula is presented as a semimartingale-type decomposition for smooth function of Brownian motion and the author shows using Mathematica plots how the higher order terms in the second-order Taylor expansion vanish asymptotically. This article is not merely Mathematica code for Ito calculus, for the author gives an example of how to use the package in a hedging problem.

The article "Option Valuation" is a more detailed overview of how to use Mathematica in the context of the Black-Scholes model to perform options valuation and risk management. Heavy use is made of the graphics capability of Mathematica to illustrate how option values change as a function of stock price and time of expiration. The author also shows how Mathematica can be used as a OO-language to treat options as self-contained objects with accessor functions. He does however state that Mathematica does not live up to the OO toolkits available elsewhere, contrary to my experience. He closes the article with a consideration of how to use Mathematica to value options that can be exercised before expiry, the binomial model playing the central role in the discussion. It is here in particular that the performance of Mathematica is readily felt. The numerical number-crunching needed to do the calculations in these types of models cannot be done in Mathematica efficiently and profitably.

Book Description

Mathematica's diverse capabilities make it particularly well suited to perform the many calculations encountered in statistics. This book introduces Mathematica for various types of statistical computations. It covers a broad range of topics, and should appeal to both students and professional statisticians.

Key Features
* Comprehensive: Covers the use of Mathematica for applications ranging from descriptive statistics, through multiple regression and nonparametric methods; uses virtually all of Mathematica's built-in statistical commands, as well as those contained in various Mathematica packages; Additionally, the authors have written numerous procedures to extend Mathematica's capabilities, which are also included on the CD-ROM
* Easy to read: Uses "by example" approach authors have used in several other books about Mathematica: works for beginners and experts alike
* Applied: Examples from diverse disciplines, including biostatistics, business, statistics, econometrics, engineering, and psychology
* Up-to-date: Compatible with Mathematica Version 3
* Includes CD-ROM: with all Mathematica inputs from text and also numerous procedures to extend Mathematica's built-in, statistical capabilities

Customer Reviews:

Be forewarned.......2005-12-17

This book is slightly useful for people who know a little about Mathematica and more about statistics. The book is moderately useful in gaining some idea about how to go about doing statistics with Mathematica.

However, I hope that the editors involved with the publication of this text from Academic Press have all gone back to work at something that does not require eyesight and an ability to read simple words. Others have mentioned the ubiquitous errors. I have never encountered a published final text that is more rife with errors. I've used Mathematica to actually calculate the number of errors in the text (couldn't do it in my head), and the answer is 1.34252x10^14. There are few pages that do not contain at least one error, some, numerous. For example, on page 83 the output of has 6.43041 <10^8, instead of 6.43041x10^8. Again, hardly impenetrable but evidence of extraodinary sloppiness. On page 81, we see Statistics'DataManipulation' which should read Statistics`DataManipulation`. On and on.

The most infuriating thing is that NONE of the text files on the data disk match precisely what is described in the text. Files are referred to by name and they do not exist. Or the data exists in an altered form in some other file. You have to spend your time doing with the editors should have ensured, and that is correctly matching the data with the text.
In short, the book should be taken off the market and either edited or consigned to the flames.

This is a good book........2001-10-26

If you¡¯ve studied statistics before, then this is a good reference book to do statistical analysis with mathematica. This book has many examples and considerably decent explanations. I found some errors in data in the accompanying CD. One (census.txt) of them is very bad; others are annoying but can be overcome easily. Also this book has several typos, which are annoying. However, this book helps readers harness the power of mathematica for statistics.

Statistics with Mathematica.......2001-01-01

Statistics with Mathematica (which I'll refer to as "SwM") is a book for someone who knows something about Mathematica and something about statistics--the more known, the better. SwM is neither a comprehensive tutorial on Mathematica nor on statistics. Rather, SwM illustrates by example how to perform statistical operations and produce graphs using Mathematica. SwM is both a tutorial and a reference book. SwM was written for Version 3 (or later) of Mathematica, although one can purportedly squeak by with Version 2.2.

A word of advice: Before you buy this book, decide whether you have some compelling reason to perform statistical analyses and make graphs using Mathematica, as opposed to, say, Excel.

I found the large number of typos, oversights, and the poor integration of the accompanying CD quite annoying. To the reader familiar with Mathematica, many of the typos are glaring and easy to correct. Other typos, such as incorrect page numbers listed in the index, are more problematic.

Knowledge of Mathematica will also see you through most of the oversights. For example, if you already understand why you must first load a Mathematica Standard Add-on Package before attempting to use one of its functions, you will not need such a reminder in SwM. A reminder is given, but many pages too late.

SwM's preface promises that all Mathematica input is included on the accompanying CD. That is simply not so--some files referred to in the text are not on the CD. However, if you don't mind typing a few missing files, you can make them yourself. The CD, oddly titled "UNTITLED_CD", contains two folders and a total of 60 files. Most files are cryptically named and are not referenced in the text nor vice versa. That's where the fun begins. The SwM text will refer you to an author-defined procedure, tell you to locate it on the CD, but fail to mention the name of the requisite CD file.

A redeeming feature of SwM is the collection of ready-to-use author-defined procedures available to the reader. Some are simple and obvious, while others, such the "Box and Whisker" plotters, would require some effort to write from scratch. The authors' procedures help both by extending the use of Mathematica's add-ons and by illustrating how one might write or modify such procedures.

SwM includes a chapter on data manipulation that illustrates how to transfer data from a text file to Mathematica list variables where the data can be worked upon. SwM, however, does not address how to transfer data from Excel or other commonly used data base applications.

SwM covers a wide gamut of statistical tools including descriptive statistics, univariate and multivariate methods, data smoothing and time series, probability and probability distributions, simulation, inferential procedures, analysis of variance, and regression and correlation, as well as the graphic representation of data and its attributes.

As far as I know, SwM is the only book of its kind that is devoted to statistical analysis via Mathematica. While sloppy editing does leave SwM frustrating to use, the reader could reorganize and index the CD's Notebook files and eventually find SwM to be a favorite reference.

Average customer rating:
Statistics with Mathematica
Martha L. Abell
Manufacturer: Academic Press
ProductGroup: Book
Binding: Paperback
ASIN: B000OHIDWQ

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