Book Description

Called the "bible of applied statistics," the first two editions of the Handbook of Parametric and Nonparametric Statistical Procedures were unsurpassed in accessibility, practicality, and scope. Now author David Sheskin has gone several steps further and added even more tests, more examples, and more background information-more than 200 pages of new material.The Third Edition provides unparalleled, up-to-date coverage of over 130 parametric and nonparametric statistical procedures as well as many practical and theoretical issues relevant to statistical analysis. If you need to…·Decide what method of analysis to use·Use a particular test for the first time·Distinguish acceptable from unacceptable research·Interpret and better understand the results of pubished studies…the Handbook of Parametric and Nonparametric Statistical Procedures will help you get the job done. ... Read more

Reviews (5)

Useful reference book
Got it as a reference book to help me understand statistical tests. Havent used it much in my daily work, but its very comforting to know that its there. Quite readable, and extremely bulky to handle. Guess this will go on to be a classic in the field ..sad reality is that most of the methods discussed are already in programs like Minitab & S-Plus, so you can do most of the analysis without slogging through the theory.

Comprehensive, valuable reference
This is an excellent, exceptionally comprehensive, and well-structured reference on a wide range of inferential tests and measures of association, which is ideal for the applied scientist. After a few useful introductory chapters that provide definitions and outline the main concepts involved in inferential statistics, the various tests are covered chapter by chapter. Each chapter contains sections describing:
1. the hypotheses evaluated and relevant background information;
2. examples of the kind of problems that can be addressed using the test
3. the null and alternative hypotheses;
4. computation (including meticulously worked out examples so the reader can follow the precise workings);
5. an extensive set of notes describing the interpretation of the results, the assumptions of the test, the robustness of the test to violations of those assumptions, and comparisons with alternative tests;
6. a set of references.
A set of decision tables are provided to assist the user in selecting the appropriate test, and there are additional extensive discussions in the various chapters to assist further if required. The book also includes an extensive list of look-up tables for significance testing. An additional valuable feature of the book is that in the chapter on the nonparametric test for a difference in medians of two populations (Mann-Whitney U-test) there is included discussions about permutation and randomization tests.

The target audience of the book is the practioner rather than the theoretician. The book aims to assist in the selection of an appropriate test and the interpretation of the test results rather than on a theoretical discussion of the test. The text is exceptionally clearly written, and is highly accessible to non-experts in statistics. There is a minimum of equations, which are supplied only where necessary. While it is not that hard to find a few editorial omissions, the book does seem to have been edited carefully, and I have as yet stumbled across only trivial errors. If I were forced to find any criticism, about the only thing I could say is that at the top of the page the chapter headings are listed purely in terms of test number without listing the test name, which sometimes makes it a little harder to find the test of interest.

I make absolutely no hesitation in recommending this book to anyone who makes use of inferential statistics.

Backbone for statistical analysis
Excellent book for handling all common and uncommon stats tests. Plenty of examples for application, an overview for each. This book is good for those that have had stats and need a reference guide on them later. I would not recommend this for anyone that has not actaully formally studied higher end stats.

Superb handbook
"One stop shopping" for information on statistical testing

A great aid for understanding the use of statistical tests.
From a student's point of view, this book contains numerous aids to assist in understanding the application of many statistical tests. For example, the decision charts on pages 27-30 help to determine what tests are applicable for analysis given the type of data the researcher plans to obtain in the study. I might decide that the use of the Kruskal-Wallis is appropriate. The chart refers me to Test 17, which is on page 396. I can go to that page, and get a complete plain-language explanation of the test and what it measures. Examples are provided for each test to determine appropriateness, and this section is followed by an example with computations. A complete analysis of the data and a discussion of the test ensues. All of the necessary tables for computation are included in appendices. I am a complete novice at statistics, and this book has helped me to understand material in classroom lectures. ... Read more

Book Description

This tried-and-true book of differential equations expands upon the authors' Differential Equations: Computing and Modeling, 2nd Edition. It covers the core concepts and techniques of elementary linear algebra—matrices and linear systems, vector spaces, eigensystems, and matrix exponentials—that are needed for a careful introduction to linear equations. Complimenting this solid foundation, the book emphasizes mathematical modeling of real-world phenomena, and offers a fresh new computational flavor evident in figures, examples, problems, and projects throughout.Chapter topics include: first order differential equations, mathematical models and numerical methods, linear systems and matrices, vector spaces, linear equations of higher order, eigenvalues and eigenvectors, linear systems of differential equations, matrix exponential methods, and nonlinear systems and phenomena.A geometric visualization for those interested in science and engineering. ... Read more

Book Description

The market-leading textbook for the course, Winston's OPERATIONS RESEARCH owes much of its success to its practical orientation and consistent emphasis on model formulation and model building. It moves beyond a mere study of algorithms without sacrificing the rigor that faculty desire. As in every edition, Winston reinforces the book's successful features and coverage with the most recent developments in the field. The Student Suite CD-ROM, which now accompanies every new copy of the text, contains the latest versions of commercial software for optimization, simulation, and decision analysis. ... Read more

Book Description

This book illustrates basic statistical concepts with extensive applications in engineering and scientific contexts. The book includes optional theoretical exercises, allowing readers who choose to emphasize theory to do so with requiring additional materials. The fourth edition contains SAS and MINITAB computer printout results for all analyses performed—plus new exercises based on magazine and journal articles and news reports. KEY TOPICS: A section on "Detecting Normal Distributions" (Chapter 5) gives readers insights on when it is reasonable to assume that underlying data is normally distributed. There is a comprehensive example on model building (Chapter 13) and emphasis on the regression approach to a Nova (also presents the traditional approach). There are two sections discussing principles of experimental design, i.e., noise-reducing and volume-increasing design, a section on "Total Quality Management" and coverage of statistical computing. There are optional, calculus-based theoretical exercises, and real data sets, extracted from scientific studies, are provided in an appendix. Numerical answers to all applied exercises are included in an appendix—giving readers immediate feedback on their work. ... Read more

Reviews (2)

Good for intuition
I think this book is very good for grasping the concepts and intuition behind the mathematical formalisms. Perhaps it should be used with another more theoretical book (Meyer, for instance). It is useful not only for engineering students.

Good book without the unnecessary confusion added
The author adds unnecessary confusion by ignoring variable naming conventions. In some places he uses "y" as the independent variable name, while in other places, he uses "x". I have never seen f(y) on the vertical axes but yet the author uses P(y) on the vertical axes. It seems the only equation he got correct, according to convention, was the historical y=mx+b. This book should be dreastically updated to conform to standard variable naming conventions. After eliminating the variable naming confusion, I think this book will be an excellent book to read and learn ... Read more

Reviews (3)

Can't beat it
...This book is the source of all you need. It's hard going at times, but so's the subject. The book's 15 years old and remains the best guide to the analysis of correlated data. It's a reference book, one I value as much as a good dictionary. To use it as a text would be misguided unless the instruction was aimed at a sophisticated audience.

Best MRC Book Ever
I agree with the previous reviewer that there are times when the exposition in the book gets a bit intense; but c'mon! We're dealing with statistics. You gotta sweat a bit. That's when learning happens. In my opinion the book is extremely clearly written. And although you may have to re-read a few sentences a few times, the basic tools for understanding most every major aspect of MRC is embedded in the text. In sum, this was a great book that I read as a 2nd-year graduate student in psychology. Unlike the first reviewer, I turned to this text when I got confused during the course lectures!

MRC Analysis---good book overall
Cohen and Cohen's MRC analysis book is well versed and easy to understand for someone that is familiar with MRC terminology, however, for first year graduate students, the text is very equivocal. The book is lacking ample illustrations of complex problems, leaving students to rely on outside sources. Also, the book uses unfamiliar symbols that do not correspond with other MRC books, which intensifies the confusion level of the students even more.

Overall, the text is a great addition to a statistical library, and this reviewer recommends it, in spite of being a sub-par book for first year graduate students. ... Read more

Book Description

Comprised of three information-packed parts, Pairs Trading presents an in-depth look at the various aspects of these strategies and provides quantitative tools to assist in their analysis. The first part of this comprehensive resource sets the context for the rest of the book by introducing preliminary material on some key topics, including time series, factor models, and Kalman filtering.

After presenting the broad ideas and concepts of this trading method, Pairs Trading delves into two different versions of pairs trading in the equity markets–statistical arbitrage pairs trading and risk arbitrage. Part II of this book details statistical arbitrage pairs trading, which is a relative value arbitrage on two securities based on the premise that there is a long-run equilibrium between the prices of the stocks comprising the pair. Part III moves on to illustrate the trading techniques and strategies associated with risk arbitrage–the widely practiced arbitrage technique that involves pairs trading arising in the context of corporate events, especially mergers and acquisitions.

Written in a straightforward and accessible style, Pairs Trading provides a framework that will allow you to boost the bottom line of any portfolio. ... Read more

Amazon.com

"There is terror in numbers," writes Darrell Huff in How to Lie with Statistics. And nowhere does this terror translate to blind acceptance of authority more than in the slippery world of averages, correlations, graphs, and trends. Huff sought to break through "the daze that follows the collision of statistics with the human mind" with this slim volume, first published in 1954. The book remains relevant as a wake-up call for people unaccustomed to examining the endless flow of numbers pouring from Wall Street, Madison Avenue, and everywhere else someone has an axe to grind, a point to prove, or a product to sell. "The secret language of statistics, so appealing in a fact-minded culture, is employed to sensationalize, inflate, confuse, and oversimplify," warns Huff.

Although many of the examples used in the book are charmingly dated, the cautions are timeless. Statistics are rife with opportunities for misuse, from "gee-whiz graphs" that add nonexistent drama to trends, to "results" detached from their method and meaning, to statistics' ultimate bugaboo--faulty cause-and-effect reasoning. Huff's tone is tolerant and amused, but no-nonsense. Like a lecturing father, he expects you tolearn something useful from the book, and start applying it every day. Never be a sucker again, he cries!

Even if you can't find a source of demonstrable bias, allow yourself some degree of skepticism about the results as long as there is a possibility of bias somewhere. There always is.

Read How to Lie with Statistics. Whether you encounter statistics at work, at school, or in advertising, you'll remember its simple lessons. Don't be terrorized by numbers, Huff implores. "The fact is that, despite its mathematical base, statistics is as much an art as it is a science." --Therese Littleton ... Read more

Reviews (50)

Some things never change
How to Lie with Statistics by Darrell Huff gives an explanation of common statistical errors. The book is clearly written and is understandable to a reader without a mathematics or statistics background. At only one hundred and forty two pages the book is a quick and easy read.

The book was originally published in 1954. The many copious examples were current at the time of writing, but are extremely dated now. Depending on the readers attitude this may be distracting, or faintly amusing. The advanced age of the examples does not make the text any harder to understand.

While the examples are dated, the concepts appear to be timeless. The same statistical manipulations still seem to be going on nearly fifty years later. The Author covers a wide range of statistical errors, or abuse. All of the types of errors will be familiar to anyone who pays attention to the news, or has seen an advertisement that uses numbers.

How to Lie with Statistics gives the reader the knowledge to detect common statistical skulduggery. If this knowledge were more widely spread, perhaps advertisers, political spinmiesters and sloppy journalists would not be able to get away with that sort of abuse.

Clear, Concise, and Fun
How to Lie with Statistics is a fun and informative look at the was in which statisticians try to decieve the public with misleading statistics. Every chapter contains plenty of real-world examles that provide excellent insight into the concepts. The book is a quick read (only 142 pages) and it holds the reader's attention; both are necessities for an educational work. How to Lie with Statistics is perfect for the beginning statistics student or anyone who wants to learn how they can be decieved through the manipulation of numbers. The reading level and math make this more appropriate for high school or college students than for younger students. Using three randomly selected paragraphs, the mean Flesch-Kincaid grade level was 10.4; thus this book is excellent for sophomores or advanced freshman. Although the writing is a little dated (1954), it is still clear and highly relevant. Overall, this is a highly recommended and worthwhile read.

Defend yourself from the number-tossers
How to Lie with Statistics, by Darrel Huff, should be required reading for everyone. The cachet of numbers are used all the time in modern society. Usually to end arguments--after all, who can argue with "facts"? Huff shows how the same set of numbers can be tweaked to show three different outcomes, depending on where you start and what you use. The fundamental lesson I learned from this book is that mathematical calculation involves a whole set of conditions, and any number derived from such a calculation is meaningless without understanding those conditions.

He also mentions that colleagues have told him that the flurry of meaningless statistics is due to incompetence--he dispatches this argument with a simple query: "Why, then, do the numbers almost always favor the person quoting them?" Huff also provides five questions (not unlike the five d's of dodgeball) for readers to ask, when confronted with a statistic:

1. Who says so?

2. How does he know?

3. What's missing?

4. Did somebody change the subject?

5. Does it make sense?

All this is wrapped up in a book with simple examples (no math beyond arithmetic, really) and quaint 1950s prose. In addition humor runs from the beginning (the dedication is "To my wife with good reason") to the end (on page 135, Huff says "Almost anybody can claim to be first in something if he is not too particular what it is"). This book is well worth a couple hours of your time.

Tools of Lying Liars and those who believe
(...)

One particular "statistic" tells it all. "A study showed that 98% of all heroin addicts started out by drinking milk. Therefore the conclusion is that milk consumption leads to heroin addiction and to protect society we should ban the sale of milk."

It seems pretty farfetched, but the (il)logic applied above is still used today to sell products, ideas and even legislation that controls our lives.

My advice, Read This Book and learn to see beyond the faulty studies and conclusions still used to manipulate us for other's gain!

An Entertaining Primer on the Validity of Statistics
Although "How to Lie with Statistics" is a bit dated (having been written in the 1950's), the principles it puts forth are still valid today--if not moreso than ever--and the material is delivered in clear, concise, and even entertaining anecdotes and illustrations.

How often do you hear statistics bandied about in the media or used to try to prove some special-interest point? "Of course" the people quoting the figures must be right with numbers on their sides... until you look at just how those numbers were arrived at.

This book isn't truly a guide on how to lie with statistics, but it is an excellent text that informs the reader both how others will lie to them using statistics and on how to interpret the validity of purported statistical data. ... Read more

Book Description

This example-rich reference fosters a smooth transition from elementary ordinary differential equations to more advanced concepts. Asmar's relaxed style and emphasis on applications make the material accessible even to readers with limited exposure to topics beyond calculus. Encourages computer for illustrating results and applications, but is also suitable for use without computer access. Contains more engineering and physics applications, and more mathematical proofs and theory of partial differential equations, than the first edition. Offers a large number of exercises per section. Provides marginal comments and remarks throughout with insightful remarks, keys to following the material, and formulas recalled for the reader's convenience. Offers Mathematica files available for download from the author's website. A useful reference for engineers or anyone who needs to brush up on partial differential equations.

Reviews (3)

Partial Differential Equations and Boundary Value Problems
I think this book is Possibly the best Mathematic book for Engineer I've ever read. This is due to the fact that the material is so much clear and the examples are so easy to follow. The book's explanation is precise and accurate. The exercises on every chapter are helpful. I practise almost most of the exercise problems. In fact, I score an "A" on the first Test. I will recommend it to everyone without hesitation.

Initial impressions
Nakhle: Just a quick note to thank you for your book! It arrived Thursday, and I've been reading it and doing the exercises both on paper and in Mathematica 3.0. After a quick review of the whole book and a thorough reading of the first 70 pages so far, I can say I just love it! If I'd only had a book like this in college and graduate school I'd have become a much better electrical engineer. Yours is one of the best expositions of both Fourier series and partial differential equations I've used. Although I haven't gotten very far into the boundary value problems and the orthogonal functions areas of the book yet, my initial review indicates they will be excellent also. I am enjoying your book immensely, and I thank you very much for it. I'll update this with a more thorough review when I have a chance to finish the book, but I wanted to share my initial impressions so others might weigh them into their own decisions to get this excellent book.

A clear introduction to PDEs, Fourier series
This text not only provides a simple and easy-to- read-the-first-time guide to solving PDEs with Fourier series, it also is chock-full with all the necessary details and includes many interesting problems. I took a course out of this book as a sophomore in college and found it very interesting and useful. The style and difficulty is very similar to a typical undergraduate ordinary differential equations book, except this is better organized.

The subjects include a small bit on characteristics for first-order equations, a chapter on trigonometric series, PDEs in rectangular, polar, and spherical systems and associated eigenfunction expansions, Sturm-Liouville theory, the fourier transform, Laplace/Hankel transforms for PDEs, grid-type numerical methods, sampling & discrete Fourier analysis, and quantum mechanics (the Schrödinger equation).

This book is definitely great for applied mathematicians, physicists, or engineers who really need a solid introduction to the topic, written by someone who knows all the details. Any treatment in "mathematical physics" courses on PDEs will fall short of this book's content.

Of particular importance are the inclusion of special sections for Bessel functions, Legendre polynomials, associated Legendre functions, spherical harmonics, etc. All the details of solution and many exercises are included.

The most interesting parts of the book are towards the end, with the Sampling Theorem and discrete Fourier transform; and the proof of Heisenberg's uncertainty principle.

This book is also useful for more theoretical mathematicians or mathematical physicists who need an introduction to PDEs before taking a more difficult course on general theory.

In short, I think that even though this book is of great utility to non-mathematicians, it is proper to learn these concepts and techniques in a proper math setting where care is taken. This text is a solid foundation for confident application and a springboard towards more advanced subjects. ... Read more

Book Description

This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied in economics, engineering, and the natural and social sciences. The book assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This second edition contains detailed instructions on the use of the new totally windows-based computer package ITSM2000, the student version of which is included with the text. Expanded treatments are also given of several topics treated only briefly in the first edition. These include regression with time series errors, which plays an important role in forecasting and inference, and ARCH and GARCH models, which are widely used for the modeling of financial time series. These models can be fitted using the new version of ITSM. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include the Burg and Hannan-Rissanen algorithms, unit roots, the EM algorithm, structural models, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introductions are also given to cointegration and to non-linear, continuous-time and long-memory models. ... Read more

Reviews (4)

Great book for a great price
This is one of those books that you can't find much cons to it. The book is inexpensive, and it's unbelievably lightweight. The material is rich, and yet easy to understand. The author actually brings you step by step from elementary to theorectical proofs.

excellent introduction for students and practitioners
In contrast to their graduate text "Time Series: Theory and Methods" this book is more elementary and introductory and is pitched at the advanced undergraduate level requiring only calculus, elementary statistics and matrix algebra. It gives very good coverage to a wide variety of time series models and includes some nonstationary models. In this second edition the chapter on nonstationary models includes the latest coverage of ARCH and GARCH models presented in a way that I found very accessible.

Computations are done with ITSM and in this edition the ITSM 2000 version 7.0 edition is included on a CD so that students can reproduce the authors' calculations and run analyses of their own.

Another nice feature of the text that distinguishes it from other texts at this level is the introduction of multivariate time series, coverage of state space models, chaos and cointegration. Ideas are illustrated with examples. Important theory is discussed but is kept brief and theorems and proofs are not given to the extent of their other more theoretical text.

Excellent introduction on time series analysis
Very good introductory book to ARMA models. Full of real-life examples that provide some intuitive insight about the issues that may arise when modelling time series and forecasting. Requires some initial knowledge in statistics and algebra but if you're involved in time series modelling, it should be your first book.

Best introduction to time series analysis
Very good introductory book to ARMA models. Full of real-life examples that provide some intuitive insight about the issues that may arise when modelling time series and forecasting. Requires some initial knowledge in statistics and algebra but if you're involved in time series modelling, it should be your first book. ... Read more

Book Description

This text gives a comprehensive survey of modern techniques in the theoretical study of partial differential equations (PDEs) with particular emphasis on nonlinear equations. The exposition is divided into three parts: 1) representation formulas for solutions, 2) theory for linear partial differential equations, and 3) theory for nonlinear partial differential equations.

Included are complete treatments of the method of characteristics; energy methods within Sobolev spaces; regularity for second-order elliptic, parabolic, and hyperbolic equations; maximum principles; the multidimensional calculus of variations; viscosity solutions of Hamilton-Jacobi equations; shock waves and entropy criteria for conservation laws; and much more.

The author summarizes the relevant mathematics required to understand current research in PDEs, especially nonlinear PDEs. While he has reworked and simplified much of the classical theory (particularly the method of characteristics), he emphasizes the modern interplay between functional analytic insights and calculus-type estimates within the context of Sobolev spaces. Treatment of all topics is complete and self-contained. The book's wide scope and clear exposition make it a suitable text for a graduate course in PDEs. ... Read more

Reviews (6)

Excellent
Evans succeded in writing a text on partial differential equations which can serve a broad spectrum of users: from pure mathematicians interested in hard theorems about the properties of solutions to various types of PDEs to sophisticated practitioners interested in solving specific problems leading to PDEs. The book covers in sufficient detail and great clarity the basic types of PDEs including modern topics such as optimal control, Hamilton-Jacobi equations, and viscosity solutions. Emphasis is pretty evenly distributed between general qualitative properties of solutions, and techniques for explicit construction of solutions in representative cases.

PDE making sense
This is a textbook for a first-year graduate course in PDE (for mathematics students). You should take courses in analysis (on the level of Rudin) and measure theory before you expect to understand everything in this book.

This is by far the best book on PDE. The text is extremely clear, and most of the rather technical proofs are prefaced with "heuristic" calculations to help the reader understand what is going on. The chapter on the calculus of variations is the best exposition I have found of the subject, and Evans completely dispenses with the awful "delta" notation which never made any sense.

The text doesn't make much use of the Fourier transform and doesn't even mention distributions, and this gives his book a definite nonlinear flavor (which is a good thing). This should become the standard introduction to PDE on the graduate level.

Dense, but quite good
This book is a mathematician's book and not an engineer's--it hasn't a bit of material on approximating solutions of PDEs (which subject could fill several volumes by itself), and devotes a great deal of space to proving existence, regularity, and other properties of solutions to non-linear PDEs. The exposition is extremely compressed (many moderately difficult proofs are reduced to a paragraph or two).

It is also very much a graduate course (as the title indicates). Undergraduate students are advised to stay away unless they have excellent teachers, or are very good, or both.

difficult
As a graduate student in engineering, I found this book to be somewhat difficult to understand. That in itself isn't a major problem, but I have just found other books which present the material in a much clearer fashion. Part of the problem is Evans' fascination with non-linear equations to the point of muddling even simple formulations.

This will become the standard text in PDE
This is a very well written textbook for graduate-level students as well as an excellent reference for researchers. The outlook of the author, a leader in his field, is non-linear and very broad and includes maechanics and geometry. Any department library needs this book. ... Read more

Book Description

Going beyond the conventional mathematics of probability theory, this study views the subject in a wider context. It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information. ... Read more

Reviews (7)

Ontological and Epistomological Probability
I read this book before it was published; I downloaded it from a WU website. It has been of immense use to me in my career, it is a very practical book. Other reviews that say Dr. Jaynes' ideas are at odds with traditional measure theoretic probability are mistaken. Dr. Jaynes is a true Baysian. A Baysian is one who believes that probabilities do not model serendipity in nature, but do model subjective certainty. The Bayesian concept of probability is epistomological, i.e. the uncertainty is in our minds, not in objective reality. Traditional probability takes the reverse view: probabilities model unpredictable events, they are a model of objective reality like any science, i.e. probabilities are ontological. The trick is to realize the two are not mutually exclusive! There can be true ontological randomness in nature, and our minds can have uncertainty from incomplete knowledge as well. Probability theory as a branch of mathematics makes no claim what it models. The beauty is that probabiltity distributions integrate the two seamlessly. Thus, it is perfectly valid to put a distribution on an unknown parameter, epistomologically unknown, and derive that distribution from an experiment with, presumably, ontological randomness. Dr. Jaynes' book is well worth reading for the many case studies he presents. His background as a physicist is key to understanding some of the esoteric philisophical points.

The most important book on probability theory in decades
Reading this book is an exhilarating intellectual adventure. I found that it shed light on many mysteries and answered questions that had long troubled me. It contains the clearest exposition of the fundamentals of probability theory that I have ever encountered, and its chatty style is a pleasure to read. Jaynes the teacher collaborates fully with Jaynes the scientist in this book, and at times you feel as if the author is standing before you at the blackboard, chalk in hand, giving you a private lesson. Jaynes's advice on avoiding errors in the application of probability theory -- reinforced in many examples throughout the book -- is by itself well worth the price of the book.

If you deal at all with probability theory, statistics, data analysis, pattern recognition, automated diagnosis -- in short, any form of reasoning from inconclusive or uncertain information -- you need to read this book. It will give you new perspectives on these problems.

The downside to the book is that Jaynes died before he had a chance to finish it, and the editor, although capable and qualified to fill in the missing pieces, was understandably unwilling to inject himself into Jaynes's book. One result is that the quality of exposition suffers in some of the later chapters; furthermore, the author is not in a position to issue errata to correct various minor errors. Volunteer efforts are underway to remedy these problems -- those who buy the book may want to visit the "Unofficial Errata and Commentary" website for it, or check out the etjaynesstudy mailing list at Yahoo groups.

Truthful
it offers a mathematical discussion of probability
from the point of view of information theory. It argues
against the frequentist approach. The author is absolutely
right: probability has meaning only as incomplete
knowledge (but still objective). Any frequentist approach
is problematic. A real diamond.

Invaluable
This book has been on the web in unfinished form for a number of years and has shaped my scientific thinking more than any other book. I believe it constitutes one of the most important scientific texts of the last hundred years. It convincingly shows that "statistics", "statistical inference", "Bayesian inference", "probability theory", "maximum entropy methods" , and "statistical mechanics" are all parts of a large coherent theory that is the unique consistent extension of logic to propositions that have degrees of plausibility attached to them. This is already a theoretical accomplishment of epic proportions. But in addition, the book shows how one actually solves real world problems within this frame work, and in doing so shows what a vastly wider array of problems is addressable within this frame work than in any of the forementioned particular fields.
If you work in any field where on needs to "reason with incomplete information" this book is invaluable.

As others have already mentioned, Jaynes never finished this book. The editor decided to "fill in" the missing parts by putting excercises that, when finished by the reader, provide what (so the editor guesses) Jaynes left out. I find this solution a bit disappointing. The excercises don't take away the impression that holes are left in the text. It would have been better if the editor had written the missing parts and then printed those in different font so as to indicate that these parts were not written by Jaynes. Better still would have been if the editor had invited researchers that are intimately familiar with Jaynes' work and the topic of each of the missing pieces to submit text for the missing pieces. The editor could then have chosen from these to provide a "best guess" for what Jaynes might have written.

Finally, there is the issue of Jaynes' writing style. This is of course largely a matter of taste. I personally like his writing style very much because it is clear, and not as stifly formal as most science texts. However, some readers may find his style too belligerent and polemic.

Brilliant but attended by many misunderstandings
To "pure" mathematicians, probability theory is measure theory in spaces of measure 1. To the extent to which you remain a "pure" mathematician, this book will be incomprehensible to you.

To frequentist statisticians, probability theory is the study of relative frequencies or of proportions of a population; those are "probabilities".

To Bayesian statisticians, probability theory is the study of degrees of belief. Bayesians may assign probability 1/2 to the proposition that there was life on Mars a billion years ago; frequentists will not do that because they cannot say that there was life on Mars a billion years ago in precisely half of all cases -- there are no such "cases".

To _subjective_ Bayesians, probability theory is about subjective degrees of belief. A subjective degree of belief is merely how sure you happen to be.

"Noninformative" _objective_ Bayesians assign "noninformative" probability distributions when they deal with uncertain propositions or uncertain quantities, and replace them with "informative" distributions only when they update them because of "data". "Data", in this sense, consists of the outcomes of random experiments.

"Informative" _objective_ Bayesians -- a rare species -- ask what degree of belief in an uncertain proposition is logically necessitated by whatever information one has, and they don't necessarily require that information to consist of outcomes of random experiments.

Jaynes is an "informative" objective Bayesian. This book is his defense of that position and his account of how it is to be used.

"Pure" mathematicians will not find that this book resembles that branch of "pure" mathematics that they call probability theory.

Jaynes rails against those he disagrees with at great length. Often he is right. But often he simply misunderstands them. For example, writing in the 1990s, he said that pure mathematicians reject the use of Dirac's delta function and its derivatives, and related topics. That is nonsense; the delta function has long been considered highly respectable, and required material in the graduate curriculum. Unfortunately Jaynes's misunderstandings may cause some others to misunderstand him when he is right. Statisticians are more informed than "pure" mathematicians and will disagree with Jaynes for better reasons. _Some_ statisticians will agree with him.

Jaynes has many flaws, made all the more annoying by the fact that we need to overlook them in order to understand him. His message is important. ... Read more

Book Description

This book is a valuable reference to Basic Probability and related problems, featuring unique discussions published in recent journals to support individual investigation. Chapter topics include combinatorial methods, conditional probability and independence, random variables, distributions, and simulation. For professionals in the fields of computerand actuarial science, electrical and industrial engineering,, operations research, applied mathematics, and statistics, who desire additional input to help solve the indeterministic business, government, and engineering problems they encounter at work.

Reviews (9)

VERY POOR QUALITY
This is a pathetic book. You can study as hard as you like, but you will not be able to solve the problems at the end of each section. Why? Because those problems are totally unrelated to what's explained in the chapter. I know most people say this book is good -- its because they're either paid by the publisher to praise this book or they're phd or graduate students. And please don't think I'm making a bad review because I'm a weak student. I have an excellent background in calculus and other pre-requisits for this course. I have aced most of my math courses at my university, and never have I gotten anything less than B in any math course I took. I have done over 26 credits in math for my BS in EE -- calculus, linear algebra, Differential Equations, etc and I got A in 16 and B in 10 of those credits. However when I took this course, the book is so extremely poor that I got 60 in the first test. And thereafter the professor said exams will be open book and open notes because the material is simply too poor. Only students having a very strong background in probability would understand this. For a beginner in probability, this book sucks big time.

Don't buy another!
This is an excellent reference book for anyone taking a graduate level Math Stat class. I have read Hoag & Craig, Cassella, Mood Graybill & Boes, and Mukhopadhyay, and this book is clearly the easiest to read from simple distributions to moment generating functions, to transformations, etc.

After you read this, you are going to wish the author had part II covering inferential methods.

Ghahramani has manged to find the *perfect* balance!!
You won't believe what Ghahramani has accomplished until you BUY THIS BOOK (2nd Edition)!!

Instead of trying to intimidate the student with formulas from the abyss and his superior intellect, Ghahramani matter-of-factly shows you what needs to be seen, backs it up with *excellent* examples and side remarks, provides the opportunity to complete a problem set, and moves on quickly to the next section.

What we have here is the model of efficiency: Enough substance to retain clarity without being prolix.

The axiomatic presentation of probability allows the reader to develop the mental framework needed to have a *deep* and *comprehensive* grasp of probability that can truly be called understanding...

One of the reviewers here makes some pretty bizarre claims; So for the record: I am not a Graduate Student.. actually, I am an undergraduate Aerospace Engineering Major.

Ghahramani's English is Superior -- His sentences flow easily and makes for a quick read. If you cannot learn from this book, it is because you are either Illiterate, Lazy, or Inept at BASIC math.

There is *NO* Calculus until Chapter 6! Furthermore, nearly all the symbols used in the book are actually defined and illustrated in the beginning sections of the book.

This Book is Clear, Concise, and Well-Balanced. It is not filled to the brim with overly descriptive paragraphs that emphasize all the wrong things. Gharamani knows exactly where to place the emphasis so that you dont have to spend hours trying to figure out what is important and what is not. This is THE book to have for "Mathematical Statistics 1" or "Intro to Probability".

"An Excellent Book"
Saeed Ghahramani does a fine job with this text. This is a great text for those seeking a guided introduction to the fundamental elements of probability. I am a undergraduate mathematics major & find the material in this text pleasing to read and full of examples that aide in the learning process. This text reminds me of the Springer series of mathematics texts (with it's page style, fonts, & chapters). But one peace of advice, do not read through this book quickly. Take your time and do as many examples as possible (the odd numbered review questions are answered in the back so you may check your work).

Amazing Piece of Work!
Upon opening this book, I questioned its content. I said to myself blissfully "Is this going to be a good book about probability?" After reading some of these reviews I questioned this books style. After all, Saeed Ghahramani isn't one of the best writers on mathematics out there.

This book however, is amazing. It is a piece of art. With every page, I am given a new challenging problem. Each problem is for the most advanced mind who is willing to go beyond their capabilities. Every example is great in itself, and expands the readers mind as it did to me. Let's put it this way. I was a C+ statistics student my Freshman year after the first semester. After reading this book, and completing each problem to the best of my ability, my second semester grade was an A+ I completed the course right at the top of the math class due to this wonderful book. How good is this book? It is one of the best books of our history about probability.

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(Pros:)

~"Fundamentals of Probability" is a great book. Not only does it give you fun and challenging problems, but it gives you problems which you can relate to in your everyday lives. It gives you material which will stick with you for the rest of your life. It is that good.

~Each problem is right to the point, not too long, not too short. Every problem is just as long as it needs to be making it so great.

~The authors style is nothing short of genious. Sure, it is a little straight forward, but what would you expect buying such a great piece of work. By purchasing this, you have to have some notion of probability. You can't expect to pick the book up (never learning anything about probability) and loving it. You have to have some background.

~On top of it's great content, great style, and great time notion, Fundamentals of Probability has an outstanding cover. It is really fascinating actually. Think about it, probability is a very complicated thing. The book is like lighting, that's how beautiful and shocking it is.

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(Cons:)

~As stated in the other reviews, it absolutely needs an answer booklet. I had no way of coming to the conclusion that I was right or wrong on the problems, I just assumed I was right most of the time. It doesn't take much away from the book though.

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Saeed Ghahramani might not be the most well known author, but this should win him an award. He has written the most enjoyable math book I have ever read (Mind you, I don't like to read Math books at all.) I will definately read this book again, and keep it in my collection forever. What is the probability that lighting will hit you in the head? Very low of course! What is the probability that you will not enjoy this ingenious piece of work? Refer to the above statement. ... Read more

Book Description

This example book contains C++ source programs that exercise and demonstrate all of the subroutines, procedures, and functions in Numerical Recipes in C++. The book will be a valuable aid to readers wishing to incorporate Numerical Recipes procedures and subroutines into larger programs and to conduct simple validation tests. Each example program contains comments and is prefaced by a short description of what it does and of which Numerical Recipes routines it exercises.In cases where the demonstration programs require input data, those data are also supplied. In some cases, sample output is also shown. ... Read more

Book Description

This revision of the market-leading book maintains its classic strengths: contemporary approach, flexible chapter construction, clear exposition, and outstanding problems. Like its predecessors, this revision is written from the viewpoint of the applied mathematician, focusing both on the theory and the practical applications of Differential Equations as they apply to engineering and the sciences. Sound and Accurate Exposition of Theory--special attention is made to methods of solution, analysis, and approximation. Use of technology, illustrations, and problem sets help readers develop an intuitive understanding of the material. Historical footnotes trace development of the discipline and identify outstanding individual contributions. ... Read more

Reviews (48)

Good, but a supplement is recommended
This is a good book on ordinary differential equations. Examples are very helpful to learn how to do problems. They are pretty much the best way to learn how to solve the equations. Also, there are answers to every problem in the textbook, so you can check your answer. However this book has some nuances which you should consider: Main important points on how to solve ODEs are not highlighted (only some are, and those are mostly the theorems). The important stuff IS in the chapters, but you gotta pick it out for yourself. For that reason I recommend getting some used ODE book for cheap, that has all the important concepts highlighted (Edwards/Penney comes to mind).

Great Book!
I personally liked this book. It's easy to read and study on your own without the aid of a teacher. Its weakness is perhaps the lack of demonstrations, but since I'm a physics major I wasn't extremely concerned with them.

An aggravating textbook if you think spatially
It is interesting that the reviews of this book are so polarized, probably a result of different ways of conceptualizing math. I lean very much towards spatial (three dimensional)thinking, and this book has proven utterly worthless to me.

This is unfortunate, because most aspiring engineerers think spatially, and most are required to take a differential equations course.

My specific complaints are numerous:

1) Far too few examples
2) Exremely disorganized (examples in the book will reference a formula, concept or previous example in previous sections rather than restating the problem. I spend a lot of time flipping pages back and forth, which significantly interferes with my train of thought.)
3) Essential components of an example will be presented in paragraph form, but the reader would be much better served by presenting the information in a table or at least using a block quotation.
4) The answers in the back of the book are regulary presented in an unusual form that requires unnecessary algebraic manipulation.
5) The language is unnecessarily theoretical.
6) The examples don't really present a step-by-step method for solving a problem, but devolve into further abstraction.
7) Further discussion of essential subject matter is presented in the problems section rather than in the heart of the chapter.

If you find yourself asking the questions, "What purpose does this technique serve? Why do we need to know this? How will this help me solve a problem in the real world? or Will you draw a picture of that?" then this book is likely of little value.

And if you have a bad teacher, you may just be sunk. I just bought REA's Differential Equation Problem Solver and Tennenbaum's "Ordinary Differential Equations". I hope it helps.

Great Book, Can Be improved with a few more solved problems!
This is as good as any book gets on this subject. I suggest you keep another book as backup for extra problems for you to work your way through. The explanations here are excellent, its just that there are too few solved examples to drill the idea into your head. But as far as understanding concepts goes, this is THE book on ODEs. Go for it!

sorry but no good
I'm a student that reads all my text books and relies heavy on them. This book starts off doing a great job on first order differential equations. However, as the book move on it falls short on examples,and doing a poor job explaining more advance topics. I had real trouble with the applied sections on secound order non-homogeneus equations. I have read the older additions of this book and think they were much better. Sorry !!!!! ... Read more

Book Description

Downloadable data sets:
http://www.soe.ku.edu/faculty/Salkind/stats_fpwhs/

Click 'Additional Materials' for downloadable sample chapters

The bestselling text Statistics for People Who (Think They) Hate Statistics teaches an often intimidating and difficult subject in a way that is informative, personable, and clear. Researchers and students who find themselves uncomfortable with the analysis portion of their work will appreciate this book’s unhurried pace and thorough, friendly presentation.

Salkind takes students through various statistical procedures, beginning with correlations and graphical representation of data and ending with inferential techniques and analysis of variance. In addition, there is coverage of SPSS (and data sets for hands-on experience), and a review of more advanced statistical techniques, such as reliability, validity, introductory non-parametric statistics, and more. Pedagogical features include sidebars offering additional technical information about the topic and set-off points that reinforce major themes. Finally, questions to chapter exercises and a complete glossary are located at the back of the book.

Throughout the book, Salkind offers readers:

- Difficulty Rating Index for each chapter’s material

- Tips for doing and thinking about a statistical technique

- Top Ten for everything from the best ways to create a graph to the mosteffective techniques for data collection

- Tech Talk boxes for readers who want additional details and commentary on statistical procedures

- Things to Remember offer readers reviews and reminders of how material presented earlier relates to a technique being presented

- Steps that break statistical techniques down into a clear sequence of procedures

- SPSS Tips for executing each major statistical technique –

- Time to Practice exercises at the end of each chapter, followed by complete solutions to each problem

- Appendices contain an introduction to SPSS as well as data sets (also available online) used in the completion of chapter exercises and end-of-chapter problems

Praise for the First Edition

"I liked its humorous approach, which indeed helps to reduce statistical anxiety. The design of the book is inviting and relaxing, which is a plus. The writing style is great and the presentation is appropriate for my students. A fun and well-written book, it is easy to read and use, and presents statistics in a user-friendly way. . . . I would recommend it for sure."

--Dr. Minjuan Wang, Assistant Professor of Educational Technology, San Diego State University

"Salkind’s book is in a class by itself. It is easily the best book of its kind that I have come across. I enthusiastically recommend it for any one interested in the subject, and even (and especially) for those who aren’t!" --Professor Russ Shafer-Landau, University of Wisconsin

"Statistics for People Who (Think They) Hate Statistics really makes students learn and enjoy statistics and research in general. Students especially like the Ten Commandments and Internet sites." --Professor Valerie Janesick, School of Education, Roosevelt University

"Statistics for People Who (Think They) Hate Statistics is definitely the right book for people who have to overcome that familiar anxious feeling when opening a standard statistics book and who having finally managed to do so are still not able to make much sense of it all. The book by Salkind is easy and pleasant to read and one that hardly needs any pre-knowledge of the field to be able to follow the author’s train of thoughts. Salkind has managed to bring statistics home to people who hate statistics, or thought they did." --From a review appearing in Statistical Methods in Medical Research (Arnold Publications) Dr. Andrea Winkler, Maudsley and Bethlem Hospital, London, U.K.

New to the Second Edition:

- Downloadable practice data sets

- New chapter on factorial analysis of variance

- New chapter on reliability and validity

- New section on effect size

- An entirely revised test bank instructor's manual

Reviews (2)

Very helpful BUT....
This book was great at explaining the principles behind the math. However-- THERE WERE HUGE MISTAKES!!! The formula for the correlation coefficient for example, had a misplaced parenthetical that changed the formula. As a rookie in this area I was in tears trying to figure out my homework. This was not the only error, but it certainly was the worst!!!

Otherwise, the examples make it easy to understand the concepts of statistics, and certainly made it so I was able to ace the course. I just wish it hadn't had so many errors.

At last...a book that students can follow!
This is an easy to follow, well written book that students find useful. I have used it for teaching undergraduate research and statistics and as a supplement for graduate level research. It is written on a level so that almost all students can follow it and it provides excellent examples. ... Read more

Book Description

The latest edition of this best-selling biostatistics book is bothcomprehensive and easy to read.It provides a broad andpractical overview of the statistical analysis methods used by researchers tocollect, summarize, analyze, and draw conclusions from biological researchdata. The Fourth Edition can serve as either an introduction to thediscipline for beginning students or a comprehensive procedural referencefor today's practitioners. ... Read more

Reviews (9)

The beginner's viewpoint
Frankly, I am aghast that the publisher calls this book accessible and appropriate for beginners. I purchased it as the required text for an introductory biometry class, and it has contributed very little to my understanding of biostatistical analysis. After chapter 7 (at best), it is simply incomprehensible. The mathematical notation requires far more than a high school algebra background, and the wording is extremely terse. Yes, it does offer real-world examples, and yes, it does offer a large range of statistical tables, and I am sure that it is good reference for people who are already working as statisticians and who have advanced degrees in statistics. However, it is misleading to call Zar a good introductory text - it is completely inappropriate for beginners. It is too concise in a situation where more words would be useful. Sokal and Rohlf 2nd ed. is far better; Fowler et al. also proved helpful.

A Great Desk Reference for Biologists
I have found this book more approachable and user friendly than Sokal and Rohlf. Zar is an excellent desk reference, and has solved a number of statistical problems for me. I reccomend it to anybody who regularly uses statistics in a biological context.

Ultimate Biostat Book
You will not go wrong with this book. It is the best general
biostatistical book in print. You will need to study it for it is not a cook book, but it is well written. An absolute must book.

Concise but not beginner friendly
This book is very concise and very mathemically based. It does a good job at presenting the mathematical models of statistics but it does a lousy job at explaining biostatistics in a conceptual manner. Maybe a great book for those who love mathemical models and notations but definitely not recommended for someone who is trying to understand biostatistics conceptually. If you are a scientist with a weak bacdground in statistics, you may find it a waste of time to try to understand this book.

one of the most popular introductory biostatistics books
This book is popular because it is well written and authoritative. It is written for biologists, medical students and researchers who do not have any prior knowledge of probability or statistics and may have little mathematical training as well. It serves as an introductory text providing many homework exercises. It can also be used as a reference. It is very thorough and covers most of the important topics required for biological problems. The needed probability is introduced when necessary.

There is the usual emphasis on hypothesis testing and regression. Correlation and analysis of variance are also very well covered. Important issues of sample size determination are covered and many solutions are provided in easy to use box descriptions.

As the author points out in the preface, in order to make this text a good reference it is extensive (663 pages of text followed by appendices and a large number of tables). It also includes a wealth of useful reference articles and books. Consequently, there is too much material for a one semester course. The author provides instructors with guidelines for sections to cover in an introductory course.

Notable topics covered in this text that is rarely found in introductory biostatistics books include multivariate methods especially the multivariate analysis of variance (MANOVA)and inference for circular data.

Recent developments in meta analysis, Bayesian statistics and bootstrap methods are not covered. In fact, these topics are not covered at all. Also, the important topic of missing data is omitted. Outliers are only covered briefly and just a few references are given but the major references, the texts by Hawkins and the treatise of Barnett and Lewis are neglected.

I am currently working on an elementary text that will have the advantage of some real world applications and modern developments. There are a few other elementary statistical texts for biology that are worth considering including Motulsky's "Intuitive Biostatistics" and Riffenburgh's "Statistics in Medicine". My favorite is the slightly more advanced "Practical Statistics for Medical Research" by Doug Altman. ... Read more

Book Description

The most complete manual of its kind, this handy book gives you all the formulas and calculations you are likely to need in drilling operations.New updated material includes conversion tables into metric.Separate chapters deal with calculations for drilling fluids, pressure control, and engineering.Example calculations are provided throughout.

Presented in easy-to-use, step-by-step order, Formulas and Calculations is a quick reference for day-to-day work out on the rig.It also serves as a handy study guide for drilling and well control certification courses.Virtually all the mathematics required out on the drilling rig is here in one convenient source, including formulas for pressure gradient, specific gravity, pump output, annular velocity, buoyancy factor, volume and stroke, slug weight, drill string desig