Book Description

Awarded Outstanding Academic Book by CHOICE magazine in its first edition, FORECASTING, TIME SERIES, AND REGRESSION: AN APPLIED APPROACH now appears in a fourth edition that illustrates the vital importance of forecasting and the various statistical techniques that can be used to produce them. With an emphasis on applications, this book provides both the conceptual development and practical motivation students need to effectively implement forecasts of their own.Bruce Bowerman, Richard O'Connell, and Anne Koehler clearly demonstrate the necessity of using forecasts to make intelligent decisions in marketing, finance, personnel management, production scheduling, process control, and strategic management. In addition, new technology coverage makes the latest edition the most applied text available on the market. ... Read more

Book Description

This text is designed for first courses in financial calculus aimed at students with a good background in mathematics. Key concepts such as martingales and change of measure are introduced in the discrete time framework, allowing an accessible account of Brownian motion and stochastic calculus. The Black-Scholes pricing formula is first derived in the simplest financial context. Subsequent chapters are devoted to increasing the financial sophistication of the models and instruments. The final chapter introduces more advanced topics including stock price models with jumps, and stochastic volatility. A large number of exercises and examples illustrate how the methods and concepts can be applied to realistic financial questions. ... Read more

Reviews (2)

A fascinating look at making randomness differentiable
The behavior of large economic systems is by necessity unpredictable, for if it was, then the making of speculative profit would be impossible. The movement of markets is modeled as an example of Brownian motion, which is a consequence of the random motion of molecules. This is a complex process, where the only hope to predict the future is to apply statistical methods. Therefore, this book is largely a lesson in creating statistical models of random processes that allow for calculus methods to be used to analyze them.
The primary model is that of a discrete parameter martingale, which is where different price possibilities are computed based on probabilities that the parameter will have certain values. After years of teaching calculus, this is the first book that I have read where the concentration is on using calculus to model financial systems. Without question, I learned more new material from this book than I have in at least 90% of the math books that I have read. It was fascinating to see how a non-differentiable system is modeled so that it is then possible to use the continuous methods of calculus in working with it.
This book is perfect for advanced courses in the modeling of financial markets. The amount of calculus knowledge needed to understand the material is that of the standard three course sequence that is the start of nearly all undergraduate majors. A course in statistics based on calculus is also essential, and experience in differential equations would also be helpful, although not required.

The only reason that it does not get a fifth star is that there are no solutions to the exercises. I am a firm believer that solutions to at least 1/3 the problems should be included in any mathematics book.

Published in the recreational mathematics e-mail newsletter, reprinted with permission.

No answers to the exercises
They claim there are more than 130 exercises, but don't provide solutions. You need to be a teacher to get a password from their web site to get an access to them. It's very dissapointing. What use of them? ... Read more

Book Description

"A book that describes the steps involved in a meta-analysis in an easy-to-understand format (not just as a cookbook recipe) will be a useful addition to the literature. Practical Meta-Analysis aptly fills this niche."

--ORGANIZATIONAL RESEARCH METHODS, April 2002

What research designs and methodological features qualify a study for meta-analysis and which disqualify it? What types of research reports are appropriate for the meta-analysis? What is the cultural and linguistic range of the studies to be included? By integrating and translating the current methodological and statistical work into a practical guide, the authors address these questions to provide readers with a state-of-the-art introduction to the various approaches to doing meta-analysis. Through the use of a simple metaphor, that of meta-analysis as a form of survey research in which research reports, rather than individual people, are surveyed, the authors show readers how to develop a coding form for their meta analysis, how to select and gather various research reports for the study, how to code the appropriate information about each study’s characteristics, and how to analyze the resulting data using various software packages.

Reviews (1)

Excellent Source Book
I just completed a meta-analytic study for my master's thesis, and I could not have done it without this book. The authors take very complex topics and procedures and describe them in clear, concise terms. I often used this book to help me interpret the dense text found in other books on meta-analysis, such as Hunter and Schmidt's Methods of Meta-Analysis. I also found the book helpful because it provided concrete guidelines for such issues as selecting criteria for study inclusion and developing categories for coding studies. ... Read more

Reviews (3)

On balance, this is a great book
Grimmett & Stirzaker's book, *One Thousand Exercises in Probability, 2nd ed.,* contains exercises with answers/solutions to each and every exercise covering a wide range of topics from probability. Although this book is a companion to G & S's 3rd edition of *Probability and Random Processes,* the authors strove to make the *Exercises* book stand on its own.

The 2 previous reviewers took a widely different view of this book. I wanted to have a balanced approach to reviewing this book. I hope this helps.

-- This book has exercises that cover a wide range of topics in probability. It starts from basic issues in probability and eventually covers topics like queueing, Monte Carlo (& Markov Chain Monte Carlo), Ito's lemma & financial option valuation, etc. Any one vaguely interested in probability realizes that the topics covered by Grimmett & Stirzaker are *hot topics* and very useful to those who want to try to get a sense of how important probability theory is in real life. I can't think of a comparable book that is so ambitious and covers so much useful ground in one place. [At least not one with answers to every question.]

-- I am not personally familiar with Grimmett's work (I believe he is at Cambridge University). I am, however, familiar with Strizaker's work (he is at Oxford). I consider him to be one of the finest expositers of probability theory. Stirzaker's views on probability theory (which I read in a different work) is one of the most lucid and sensible I have ever come across. Anyone seriously interested in probability should try to get exposure to Stirzaker's thoughts on the matter.

-- I believe this book is GREAT for self-study. One of the major problems I have with many math, science, engineering, and other technical books is that -- even very good books -- do not provide answers/solutions to the questions they pose. As someone who is very interested in self-study, I find a book like this one -- which has the answers/solutions to ALL of the questons -- to be extremely refreshing and welcomed.

To address the prior criticism that this book does not contain a sufficient amount of detail in the solutions .... I would suggest that such a criticism is unfair. As I pointed out above (and most people know) it is very rare to have technical books like this where there are a great deal of interesting and useful exercises given plus answers/solutions to all of the questions posed. For 2 emminent Oxbridge dons to write such a book is even more exciting.

In all fairness, Grimmett & Stirzaker wrote this book with the intent that it be used along with an appropriate probability textbook(s). Any one willing to take the time to look at the solutions given along with a companion text should be able to work out what went wrong (or right) with any question that the reader attempts to work out.

In closing, I highly recommend this book to anyone who is interested in going from a novice level at probability to a point where you can approach and solve useful problems in probability.

Well worth the effort
I appreciate the other reviewer's oppinion as it is indeed true
that some of the problems' solutions are succinct.

However it is clearly not the point of the set of books to provide
the reader with fully worked solutions to every problem. It is
often like this in maths, you just got to go for it, no matter.

If you kick off from the first chapter and attempt the problems
in increasing order of diffculty keeping the course book by your
side, you should be fine, really.

This course is very rewarding.

Lots of answers, not many solutions
I was greatly disappointed in this book. I give it two stars for providing the answers to the problems. It would get much more if it actually provided adequate solutions to the problems. It is a good book if you know basically how to do the problems and just want to check answers. If you're like me, however, you could use some guidance for starting and proceeding through the problems. The "solutions" often omit the startup steps for many of the problems; without those critical steps, the "solution" that is given (which sometimes consists of nothing but the final answer) does not make sense to the average reader. I had high hopes when I purchased this book; I thought it would be well worth my money to get solutions to the problems so I could figure out the errors in my reasoning. Unfortunately I was gravely mistaken. ... Read more

Book Description

Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background. The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. The text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research. ... Read more

Reviews (4)

The best book I've found on the topic!
This book was the text for the intro to Biostat class at Columbia University this year. It is lucid, well organized, doesn't bog down in details or equations, and gives a good introductory explanation of the basic statistical methods, their rationale for use, and their various assumptions and shortcomings.

I can't imagine trying to do stats without a copy of this book beside me - I'd be lost. If you're in need of a book to help you understand medical statistics as they are presented in the literature, you should use this book and eschew all others.

Great book for teaching med stats
I have been teaching statistical methods and epidemiology for graduate students in the health area for more than 5 years and this book is a hit. Previously I tried Armitage & Berry and got a lot of resistance from the students. Altman's book is well organized, presents the problems and their solutions in a very intuitive way, and focus on the real problems in the area. Very good for introductory courses. I usually use Kirkwood's Essentials of Medical Statistics in parallel.

excellent intermediate level treatment of biostatistics
This is a very well written and popular text on biostatistics. Altman writes for non-statisticians but the book is best suited for those with at least one prior course in statistics and those who have had mathematics through high school algebra. Emphasis is placed on the important practical problems. Good statistical designs and analyses are emphasized. The pitfalls with many published medical articles are discussed in Chapter 16.

I used this book to teach a 20 lecture course to students (engineers, clinicians and computer scientists) at Pacesetter in 1998 and at Biosense Webster in 1999 (both medical device companies that employed me as senior biostatistician). It was a good refresher course for the CRAs and engineers and it helped to make it easier for me to work with them on their statistical problems.

I have also taught a similar course to undergraduate students in the Health Science Department at Cal State Long Beach. Altman's book is a little too advanced to use as a text for that course but I did use it as a reference and covered material in Chapter 16 at the end of the course. Clear discussion of the medical literature is very important to these students and Altman does a great job!

Very valuable for consultancy
Doglas Altman's book is extremely useful for Statisticians involved in giving consultancy to non-Statisticians. I would almost say that it gives too many secrets away! Practically the whole field of Medical Statistics is covered. There is a specially good section on power calculations for clinical trials; the nomogram and examples should save a lot of time that might otherwise be spent in using formulae. Having said that, there is software around for this sort of calculation. The book contains much valuable advice on real-life advice Statistical issues, and and realistic problems (with answers) are provided for practice. kvery valuable. ... Read more

Book Description

Business Statistics for Management and Economics is an application-oriented text providing students with a solid grounding in statistical theory and allowing them to make the most of data analysis techniques. Students learn through examples and applications of the most common statistical concepts and techniques used in business, economics and management.

Book Description

The Bayesian approach to statistics is now widely accepted as theoretically sound and practically viable. Enormous advances in Bayesian methodology in recent years have resulted in a great expansion of applications of Bayesian statistics in a wide variety of fields. This important addition to the series provides a comprehensive and readable treatment of modern Bayesian theory. ... Read more

Reviews (2)

O'Hagan's Jewel
I found this book to be my constant reference.
Like Tonny's narative style and the part on NIG Priors!
Contains valuable contributions by the author
hard to find elsewhere.

Highly recommended!

Good but not excellent
This is a very good book for graduate-level courses. It is especially useful if the student took an elementary level Bayesian Statistics/Econometrics course. The organization of the chapters are different from most other books. Chapters contain between 40 and 60 "little sections," where a section can be one paragraph long. It is easy to understand what is fundamental and what is peripheral while reading the book.
However, it has a considerable number of errata. It is quite difficult to understand why the author have not prepared a list of errata and corrections. The errors are generally not conceptual, but usually mathematical typos. They also exist in some problems, which first make you think they are unsolvable. It can take some time to figure out where the error is. Moreover, errors also exist in some solutions inside chapters. The best thing the authour would do is to prepare a list of corrections on his website (this is done by many authors in the field such as Peter Lee). ... Read more

Book Description

This comprehensive introduction to business statistics balances a conceptual understanding of statistics with the real-world application of statistical methodology. The latest version of Microsoft® Excel is integrated throughout the text, showing step-by-step instructions and screen captures to enhance student learning. The authors have been writing market-leading business statistics textbooks for over 20 years and this new edition contains the same student learning features that have made ASW products best-sellers. ... Read more

Book Description

Approaching computational statistics through its theoretical aspects can be daunting. Often intimidated or distracted by the theory, researchers and students can lose sight of the actual goals and applications of the subject. What they need are its key concepts, an understanding of its methods, experience with its implementation, and practice with computational software.Focusing on the computational aspects of statistics rather than the theoretical, Computational Statistics Handbook with MATLAB uses a down-to-earth approach that makes statistics accessible to a wide range of users. The authors integrate the use of MATLAB throughout the book, allowing readers to see the actual implementation of algorithms, but also include step-by-step procedures to allow implementation with any suitable software. The book concentrates on the simulation/Monte Carlo point of view, and contains algorithms for exploratory data analysis, modeling, Monte Carlo simulation, pattern recognition, bootstrap, classification, cross-validation methods, probability density estimation, random number generation, and other computational statistics methods.Emphasis on the practical aspects of statistics, details of the latest techniques, and real implementation experience make the Computational Statistics Handbook with MATLAB more than just the first book to use MATLAB to solve computational problems in statistics. It also forms an outstanding, introduction to statistics for anyone in the many disciplines that involve data analysis. ... Read more

Reviews (6)

Good Book for me...
There were a lot of negative comments for this book on Amazon so I sort of held off the purchase of this book. However, last week I ordered the book and quickly realised it is very useful. The book may lack detailed theory but excellent references are scattered throughout if you really want to follow it up. And the book is easy reading and well written with most statistical concepts defined before they are used.

The focus of this book primarily is to explain how to work on statistics using Matlab and it provides a taste of various areas with adequate explanations and code to get started. One advantage of this book is they do not define their own notation but use the notation which is currently in vogue in academia.

If you are starting out in Matlab, are not a statistician and do not have previous experience with other packages (like Splus or R) you should definetly think about getting a copy. If you are a Stats Guru you can just read the toolbox documentation. However note that these authors provide their additional stats toolbox FREE (which is also well written) on the website which contains most of Matlab statistical functions so you could save yourself some money on the Stats toolbox.

Disappointing
I think there would be a real interest in a book on "computational statistics" and related topics that showed details of analyses and algorithms using Matlab. This book is expensive and extremely disappointing.The explanations are sparse and very weak and the m.files are usually small add-ons to functions from the Stats Toolbox.

I think in any book on this topic there have to be detailed explanations of how methods work and what their limitations are.Otherwise the reader can find themselves in a lot of trouble very quickly. There is insufficient detail either for a student coming to the topics for the first time or for someone actually wanting to analyse data.

Other books that people might want to have a look at:
1)Statistical Pattern Recognition 2nd edition . Andrew Webb.This is not oriented to any particular language.Good introduction.
2)Netlab. Ian Nabney (this has excellent Matlab functions for neural networks)
3)Modern applied statistics with S 4th edition, Venables and Ripley. This uses a different language (but which will be relatively easy for Matlab users to learn), but learning S or R (free!) makes a huge number of tools available.
4)The recent data mining book by Hand et al. This offers clear and cogent explanations.It is good for someone who does not want overly mathematical descriptions.

I haven't looked properly at the recent Hastie,Friedman and Tibishirani book yet, but you can find reviews on the Amazon page for the book.

Not very useful
My major complain was that the authors, in general, did not present algorithms clearly. Limit selections of algorithms did not help either. As a result, you cannot use this book as a reference because it just does not contain enough material. You cannot learn much about computational statistics with this book becuase the statistic methods and algorithms are not adequately presented. you cannot even write codes for your own statistic analysis with the MATLAB examples shown in the book unless you have the Statistics Toolbox.
The only persons that might be benefit from this book are those who don't want to read the Statistics Toolbox manual on line. Given that the Mathworks no longer ship printed manuals, this book may be used a companion of the Statistics Toolbox.

sloppy writing
I ordered this book assuming to get something useful, but i got the impression while reading the book that it is like a collection of notes from other books, wrapped with some matlab code. More worrying to me was that the mathematics makes a sloppy impression. For me that means I cannot grab the book to lookup something and use the code without having to be concerned on the validity. The bottomline being I will not use it for applications and the book is a waste of money.

Instantaneous Classic!
As an independent student of probability and statistics this was a great find. You get a great overview of the useful algorithms of computational statistics. The chapter on Exploratory Data Analysis with its use of multidimensional graphing was very enlightening. It's wonderful that each topic is accompanied by source code (free on-line) that lets you see exactly how it's done. It's easy to tweak the code and explore your own data as you go along. You get just enough theory to understand the algorithm and lots of good common sense and rules-of-thumb on how to best apply it. Finally, the extensive bibliography and chapter-by-chapter annotations will point you straight to the best source for more in-depth study. ... Read more

Book Description

APPLIED REGRESSION ANALYSIS focuses on the application of regression to real data and examples while employing commercial statistical and spreadsheet software. Designed for both business/economics undergraduates and MBAs, this text provides all of the core regression topics as well as optional topics including ANOVA, Time Series Forecasting, and Discriminant Analysis.While only a prior introductory statistics course is required, a review of all necessary basic statistics is provided in chapter 2. The text emphasizes the importance of understanding the assumptions of the regression model, knowing how to validate a selected model for these assumptions, knowing when and how regression might be useful in a business setting, and understanding and interpreting output from statistical packages and spreadsheets. ... Read more

Book Description

The leading reference on probabilistic methods in combinatorics-now expanded and updated

When it was first published in 1991, The Probabilistic Method became instantly the standard reference on one of the most powerful and widely used tools in combinatorics. Still without competition nearly a decade later, this new edition brings you up to speed on recent developments, while adding useful exercises and over 30ew material. It continues to emphasize the basic elements of the methodology, discussing in a remarkably clear and informal style both algorithmic and classical methods as well as modern applications.

The Probabilistic Method, Second Edition begins with basic techniques that use expectation and variance, as well as the more recent martingales and correlation inequalities, then explores areas where probabilistic techniques proved successful, including discrepancy and random graphs as well as cutting-edge topics in theoretical computer science. A series of proofs, or "probabilistic lenses," are interspersed throughout the book, offering added insight into the application of the probabilistic approach. New and revised coverage includes:
* Several improved as well as new results
* A continuous approach to discrete probabilistic problems
* Talagrand's Inequality and other novel concentration results
* A discussion of the connection between discrepancy and VC-dimension
* Several combinatorial applications of the entropy function and its properties
* A new section on the life and work of Paul Erdös-the developer of the probabilistic method ... Read more

Reviews (2)

Learn from the masters
This book shows you how to approach problems in discrete mathematics that don't seem to be probabilistic at all, and nonetheless to apply probabilistic methods to find extremely sharp results. The book is full of beautifully chosen examples worked out by the authors, who are world class researchers in this subject area. Should be on the bookshelf of everyone who uses discrete mathematics.

A very interesting book
I found this book very enjoyable to read. Although the underlying theme of the book is to demonstrate examples of proofs of existence of a property of a finite structure by showing the structure must have the property with positive probabiltiy, the book goes beyond this to cover areas such as circuit complexity and discrepancy theory that rely heavily on probabilistic arguments. A must read for anyone who wants to add probablistic tools to their toolbox for proving things about discrete structures. ... Read more

Book Description

Science abounds with problems where the data are noisy and the answer is not a straight line. Semiparametric regression analysis helps make sense of such data in application areas that include engineering, finance, medicine and public health. The book is geared towards researchers and professionals with little background in regression as well as statistically oriented scientists (biostatisticians, econometricians, quantitative social scientists, and epidemiologists) with knowledge of regression and the desire to begin using more flexible semiparametric models. ... Read more

Book Description

The use of Bayesian statistics has grown significantly in recent years, and will undoubtedly continue to do so. Applied Bayesian Modelling is the follow-up to the author’s best selling book, Bayesian Statistical Modelling, and focuses on the potential applications of Bayesian techniques in a wide range of important topics in the social and health sciences. The applications are illustrated through many real-life examples and software implementation in WINBUGS – a popular software package that offers a simplified and flexible approach to statistical modelling. The book gives detailed explanations for each example – explaining fully the choice of model for each particular problem. The book

The book provides a good introduction to Bayesian modelling and data analysis for a wide range of people involved in applied statistical analysis, including researchers and students from statistics, and the health and social sciences. The wealth of examples makes this book an ideal reference for anyone involved in statistical modelling and analysis. ... Read more

Book Description

SPSS 10.0 Guide to Data Analysis is a friendly and easy-to-understand book that enables readers to describe data, test hypotheses, and examine relationships using SPSS. Chapter exercises provide comprehensive examples of basic statistical techniques, giving readers necessary practice. Solutions to selected exercises demonstrate step-by-step procedures.MAREKT: ... Read more

Reviews (3)

Good Support Text
This is the required text for an SPSS class I am taking. The book is well written and clear. It has proven to be a helpful and useful support text to what we cover in class, especially to go deeper on certain topics. If you want to (have to) learn SPSS, I recomment this book. Take courage, SPSS is not that hard and I am even finding myself enjoying it (thanks in part to this book)!

...

SPSS 10.0 Guide to Data Analysis
This is one of the three best introductory books on SPSS that I am familiar with. The others are Data Analysis by Jeremy Foster and Discovering Statistics by Andy Field. SPSS is a powerful statistical tool and an exceptionally fine software package, its customer support is the best I have ever dealt with. Unfortunately their user manuals are not user friendly. SPSS 10.0 Guide to Data Analysis fills a gap. Norusis's book is written in a light, humerous style but addresses complex statistical concepts in an easy to understand manner. Statistics and SPSS are an arcane and diffcult subject, somehow Norusis has made her subject friendly and funny. This is not to say this is an easy book. One of the things I look for in software manuals is exercises that demonstrate the concepts of the software. The book includes a disk. There are 23 chapters in the book and exercises for 21 of those chapters. I have also seen this book on the book shelves of some of SPSS's training staff. I think that speaks highly of the quality of this book.

SPSS- Beyond just Statistics
Hi Friends, I was introduced to SPSS package during my MBA in Agri-business at MANAGE Institute-Hyderabad, India.And I was amazed with its capabilities. It can do wonders for any organization. And the book which I'm writing about just helps you to master necessary skills. But before you open the book or SPSS software, I strongly recommend you to brush up with concepts of Statistics and more importantly which tool is best for analysis. This avoids confusion in interpreting the output.

My suggestion to SPSS Inc., would be to include student version of SPSS Base free of cost to increase it's popularity. This software is not used efficiently by several organisations. The real power of SPSS lies in Syntax reference. So next time you open SPSS be prepared to explore as much as you can. wirte your queries and opinions to me at gopinathkoneti@yahoo.com ... Read more

Book Description

Chris Olsen has teamed up with Roxy Peck and Jay Devore to create INTRODUCTION TO STATISTICS AND DATA ANALYSIS. Based on STATISTICS: THE EXPLORATION OF ANALYSIS AND DATA, Fourth Edition, this new book integrates the graphing calculator and includes expanded coverage of probability. This innovative book focuses on the analysis of real data to motivate the study of statistics. Traditional in structure yet modern in approach, this book places an increased emphasis on data collection and exploratory analysis. ... Read more

Book Description

Many probability books are written by mathematicians and have the built in bias that the reader is assumed to be a mathematician coming to the material for its beauty. This textbook is geared towards beginning graduate students from a variety of disciplines whose primary focus is not necessarily mathematics for its own sake. Instead, A Probability Path is designed for those requiring a deep understanding of advanced probability for their research in statistics, applied probability, biology, operations research, mathematical finance, and engineering.

A one-semester course is laid out in an efficient and readable manner covering the core material. The first three chapters provide a functioning knowledge of measure theory. Chapter 4 discusses independence, with expectation and integration covered in Chapter 5, followed by topics on different modes of convergence, laws of large numbers with applications to statistics (quantile and distribution function estimation) and applied probability. Two subsequent chapters offer a careful treatment of convergence in distribution and the central limit theorem. The final chapter treats conditional expectation and martingales, closing with a discussion of two fundamental theorems of mathematical finance.

Like "Adventures in Stochastic Processes", Resnick's related and very successful textbook, A Probability Path is rich in appropriate examples, illustrations, and problems, and is suitable for classroom use or self-study. ... Read more

Reviews (6)

some more details
I've been reading this book along with Durrett's PROBABILITY: THEORY AND METHODS and Williams' PROBABILITY WITH MARTINGALES. I also have Billingsley's PROBABILITY AND MEASURE. All of these are good books, pitched at roughly the same level. Here are a few more specific reactions:

1) Measure theory background: Resnick & Billingsley assume no background in measure theory and interleave the relevant measure theory with probability. Durrett & Williams have appendices on measure theoretic results which cover more or less the same ground.

2) Mathematical level: Resnick is a easier than the others. He spells out lots of details in the proofs that are either left as exercises or omitted altogether in the other books. I found myself reading a statement in Resnick, asking myself why the statement was true, working out the answer easily--only to find that Resnick provided the details shortly thereafter. Sometimes this is a good thing, sometimes a little tedious.

3) Style: I'd rate Resnick below Williams and Billingsley. Williams has very elegant proofs and covers as much material as Resnick in half as much space. Billingsley is wonderfully eclectic and makes connections to lots of other areas of mathematics. Resnick is easy enough to understand, but is much more workman-like.

I think Resnick fills an important niche in this literature. I think it's a good book for teaching. I also refer to it frequently when I'm confused by something in the other books. It's thorough, relatively easy to understand, and seems to be accurate.

Measure-theoretic probability for everybody
This is indeed the best probability book I have ever read. It is the only non-elementary probability book (to my knowledge) which even non-mathematicians (e.g.: economists, engineers) may find easy to read. It provides a satisfactory treatment of measure-theoretic probability, it covers a good number of topics and it provides nice and eminently readable proofs for every theorem. All mathematics books should be written like this one: there are no oversimplifications, advanced results are presented when needed, everything is carefully proved, but it never lacks of explanations, nor too much knowledge is assumed of the reader (just a bit of calculus and elementary probability). You never have to struggle to understand things, because the author does not save words or formulas, in order to make everything clear. If I could give this book ten stars, I would. It is incomparably easier to read than Williams, Jacod and Protter, Capinski and Kopp, Ash or Billingsley. I reccomend it especially to financial economists willing to study seriously stochastic processes and stochastic differential equations.

A good instructor!
Sid Resnick provides a very readable account of probability theory. This book is more like a teacher than just a mathematics book. Resnick gives a lot of motivation for every definition and every step in the proofs. He also discusses applications of the developed theory, and gives a wealth of examples in every chapter.

One notable feature of this book, which I consider unique, is that after every definition basic facts and properties related to the definition are given in an exhaustive way. This is different than the general approach which distributes such facts into proofs, and makes it harder to follow.

A good reference for mathfinance researcher and practitioner
Resnick's "A probability path" really reduce my time to grasp the measure-theoretic probability stuff. I always recommend this book to those non-math major quants (Physics,CS,... etc) who need to have a quick look into the stochastics. However; some of the proofs may be a little bit too terse that are not easy to follow. You may need more patience and some mathematical maturity!

Excellent book !
I completely agree with Gappy's review. I wish I had entered the subject with this textbook instead of Durrett's. (The only complaint is that some of the chapter ending problems have serious errors. Sometimes the given conditions do not lead to the conclusion to be proven.) ... Read more

Book Description

This mid-level book introduces and explains statistical concepts and principles clearly, assuming minimal mathematical sophistication but avoiding a "cookbook" approach. The book also presents a broader outlook on hypothesis testing by including such often-neglected concepts as statistical power, indices and other techniques. ... Read more

Reviews (2)

It is the most understandable statistics book for beginners
I have been using this book in my statistics classes since 1990. It is so easy to understand for undergraduate students. Authors give really good examples to explain some complex subjects of statistics. These examples make the book more readable..

I would recommend this book.
This book was very informative. It explained things clearly and was useful in learning Statistics. ... Read more

Book Description

The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses.

The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms. ... Read more

Book Description

Finance is one of the fastest growing areas in the modern banking and corporate world. This, together with the sophistication of modern financial products, provides a rapidly growing impetus for new mathematical models and modern mathematical methods.Indeed, the area is an expanding source for novel and relevant "real-world" mathematics.In this book, the authors describe the modeling of financial derivative products from an applied mathematician's viewpoint, from modeling to analysis to elementary computation. The authors present a unified approach to modeling derivative products as partial differential equations, using numerical solutions where appropriate. The authors assume some mathematical background, but provide clear explanations for material beyond elementary calculus, probability, and algebra. This volume will become the standard introduction for advanced undergraduate students to this exciting new field. ... Read more

Reviews (15)

Practical, easy-to-read and useful
This book is an excellent introduction to the use of finite difference and binomial methods to the pricing of equity options - regular and exotic/path-dependent. Requires only undergraduate calculus, and provides some intuition about the finance. Has exercises and solutions for people who want to learn. The "parent" book (Option pricing: mathematical models and pricing by P. Wilmott) has more information (although a little pricey!), is in fact used by financial "quants".

Only one snag
There is no portfolio analysis which ,I think, is basic to any book in financial math.

Read Hull Instead
It seems the examples in this book are clones of those found in Hull. Odd, since the author seems to want to use more sophisticate math. Since the author can't explain calculus or properly define terms, there is doubt there is even that basic understanding. Pass on this and buy Hull instead for better clarity and better examples.

Copied Equations
Wilmott seems to have copied theoretical derivations using partial differential equations and matrix multiplication symbols. The only examples in the book use basic algebra, so it seems as if the authors don't understand how to apply theory to practice except in the most simple cases.

This book is irritatingly bad. Terms are not well defined. There are no concrete examples following the derivations as if the authors don't understand the meaning of the equations.
The information on options seems to have been copied from the many derivatives dictionaries available on the web. It's clear the authors don't know how to apply the math to price these options. It seems their understanding is equivalent to that of a parrot.

Excellent Student Introduction
This book covers the formulas describing the mathematics of derivatives, and does a good job of it. It introduces the basic concepts in a fairly comprehensive form. I also bought and recommend "Credit Derivatives" by Tavakoli, and "Credit Derivatives Pricing Models" by Schonbucher. ... Read more

Book Description

A comprehensive user-friendly introduction to biostatistics and epidemiology applied to medicine, clinical practice, and research. Features “Presenting Problems” (case studies) drawn from studies published in the medical literature, end-of-chapter, and a CD-ROM with data sets and statistical software programs. ... Read more

Reviews (8)

Pretty Good
I actually thought this book was pretty good.I haven't used the cd.The definitions are pretty clear.I use this in conjunction with Gordis' Epidemiology for quick review.I find Rothman and Greenland is not good for that.When I am thinking about research design and elements of statistical analysis this book is easy to turn to to just go over why one test may be better than another--I am a medical student with an MPH in epi who has worked on several research projects, and I think this book is pretty helpful as a simple aid in the transition from research assistant to co-investigator.

not buythis good-for-nothingbook(MUCH LESS THAN1 STAR)
If Ihadanenemy,Iwouldn'twish evenfor ananemyto buythisawfuland unusefulbook.Dosave your money. There is no any benefit in thisbook,just simple wasteoftime and money. Theauthorshave provided CD with NCSS and PASS, but forgot to describe how the reader can use this programand fulfil allcalculation. Theygive only the instruction to set up andalot of taskswithout any explanationof any actionsin these program.So, I curse any minutes of myreading, and cannot sayany good word about the book, its authors. NEVER BUY THISBOOK!!!!

Avoid it if you can
Its obvious from reading the first few chapters that the authors lack a basic understanding of the subject. For example they talk of Odds Ratio as if it was same as Relative Risk. The good thing is that they cover everything - you only have to be careful while reading it. The errata in the book is pretty obvious but the authors seem to have no time or inclination to update the website of this book.

Book Review for the 2nd edition:,
A hard plus if your looking for pregrad. introductory clinical biostatistics. However I agree with other reviews that the layout or format could be arranged more powerfully, and the mechanics explained with more and better examples with a little more detail. Some of the examples in the book are excellent. I, especially, liked the Methods for Analyzing Survival. I disliked the explanations on statististical power as well as calculating sample populations necessary (n=?)to obtain clinical significance. This book is a good bone to start knawing on, however, the meat is found in other supplemental texts; therefore, reference footnotes are needed which- nowadays- should include, reference books, journals and webpages.

Book Review for the 3rd edition: Just the Facts
1. Huge breadth: covers topics of interest to clinicians and plenty of material (see below) for aspiring researchers. Algorithms and lay-out keeps the big picture easily in view. 2. Solved problems: methodical answers, clear, instructive.3. Appropriate depth: is mathematically correct -- not oversimiplified at the cost of accuracy -- while introducing the key formulas and concepts. Much explanatory text makes the ideas clear rather than esoteric derivations. 4. Includes statistics software: menu-driven so "user friendly," has basic and advanced functions. 5. Practical approach: sample problems and exercises are modelled around cases rather than just theory. These cases have data-base directly on the accompanying software so readers may 'learn' and then 'do' immediately. 6. I learned a lot from this book :-) ... Read more