Both of my Physics instructors use this book. It is by far the most user-friendly integral table that I have seen. The tables in this book are organized in such a way that you can spend more time on your work and less time trying to find the integral.

I have a 30 year old version of this book that my mother used in college. If you want to know how to integrate any weird function, look in here. The best table of integrals i've ever seen, and lots of helpful formulas and references. A terrific reference. I have used this book for virtually all my classes as an Electrical Engineering major.

If you are a undergraduate or graduate Physics Major, this is a must-own. Schaum's Outlines, Mathematical Handbook of Formulas and Tables is OK, but if you are looking for real integral tables, you have to have this book.

Of the many recent books on wavelets, this one by Jaffard, Meyer et al stands out. This is a new edition of earlier ones, starting with a French one, then a first translation, and now this expanded version. There is lots of new material, covering new developments, both with regards to theory and applications. The authors communicate the main points in a clear and attractive way, and it stresses lucid presentation of ideas over formulas. And with an infectious enthusiasm! The presentation is especially refreshing, in that the authors do not hide behind excessive technicalities and mathematical jargon. It is the central idea that shines through. And yet the mathematically sophisticated reader is paid his dues,-- in some cases via the appendices. At that point, the technical mathematical points have been well motivated. The emphasis of the book is the mathematics behind the many algorithms that emerged from the wavelet trends since the 1980ties. And lots of new stuff added (for example JPEG-2000), right up to the present. The book is rich in applications, many of which are not found elsewhere. The inclusion of motivation and historical remarks is welcome, and makes the book enjoyable reading.

Of the many recent books on wavelets, this one
by Jaffard et al stands out. It communicates the
main points in a clear and attractive way, and it stresses lucid presentation of
ideas over formulas. The authors do not hide behind technicalities
and mathematical jargon. And yet the mathematically sophisticated
reader is paid his dues,-- in some cases via the appendices. At that point, the technical mathematical points have been well motivated. The emphasis of the book is the mathematics behind
the many algorithms that emerged from the wavelet trends
since the 1980ties.
The book is rich in applications, many of which
are not found elsewhere. The inclusion of motivation
and historical remarks is also welcome.

Although this book emphasis is on algorithms and applications, the general presentation of wavelets for signal processing is great. The introduction to the subject is really excellent and great care has been given to explaining the use of wavelets for applications in signal processing. On the other side i found the last chapters dealing with applications a little too light for being useful...

Anyway, a great book for "wavelets and applications in signal processing"...(also go to "Time-Frequency Time-scale analysis" by Patrick Flandrin which is wonderful).

then this book is for you. Do you want to know if you were discriminated against, at some confidence level? Do you want to know if the moon phase affects the NASDAQ? If Bush High School seniors score an average of 74 and Gore High School seniors score an average of 73, is Bush High really statistically better than Gore High? These are just a few of the millions of tests that can be done with this book. If you believe in the saying, "In God we trust; all others bring data," then you'll love this book, especailly if you can force your peers to use it.

This reference text gives busy people at work exactly what they want, the way they want it. They know their data needs, so they look up the clear list of tests to find the test that meets that need, and follow the simple steps to implement it: assumptions, method, equation, and a brief example. No theory, no blabbing, just to the point and ready for use. Saves time, and reading. Also, having so many tests saves the hassle of looking for a specific test somewhere in the library. This is a complete investment!

This is truely the best book on discriminant analysis in print - designed with the researcher in mind. Several appendices include actual program output from SAS, BMDP, and SPSS, which helps the user determine what to look for and how to intepret one's statistical results. Also informative is Huberty's clear distinction between predictive and descriptive discriminant analysis. The distinction is critical in practice (many researchers still get it wrong!)- -this book wil help clarify when to use one or the other.

I really enjoyed the book. It was an excellent reference book while I was working on my dissertation. I found his humor well placed and well suited to making his points. Well done.

Extremely clear, and easy to understand. It is the best introductiory book on stochastic processes for non-mathematics major. After you read this book ( one month is enough, how amazing it is!), it becomes easier to read "the first course in stochastic processes". The book focuses on the concept and intuition, instead of proof, and I find it is extremely useful for me -- CS major.

Strong recommend this great book

I randomly ran across this book in my math library trying to find an extra book to help with the difficult Stochastics Process class I was taking. Little did I know I would find a book I value as much as Douglas Kelly's Introduction to Probability. This book has applied problems and examples! It is not the dry, endless pages of confusing equations we have come to expect from Stochastics Processes books. There is something better out there! This book saved me as an undergraduate, and am now looking forward to it living up to my God like expecations as a post grad. If you are a professor, please use this book for you students. It ties together and lets you appreciate many fields such as linear analysis and even graph theory from computer science. This book will not disappoint.

This book is probably my #1 reference for kernel smoothing. It covers enough theory (bias and variance calculations) without getting stuck in mathematical details. Also the code samples are very useful and are carefully interspersed throughout the text. I think this is a great book for the applied statistician who wants to get up and running with kernel smoothing methods.

This book covers parametric and nonparametric regression, logistic regression, density estimation and smoothing, semiparametric and additive modeling. The underlying approach is to use kernel methods for smoothing and density estimation. They point to bootstrap methods as a way to put confidence bands on the density estimates. SPlus software is used to illustrate the techniques. The exposition is clear and concise and coverage is fairly broad. Interesting topics such as time series, longitudinal data analysis comparing regression curves and exploratory methods are all covered.

Ivar Ekeland is one of the better writers of popular mathematics. In "The Broken Dice," he continues with the themes explored in "Mathematics and the Unexpected." Divided into six chapters (Chance, Fate, Anticipation, Chaos, Risk and Statistics) the book is an elegant examination of the human struggle to find order in the seeming contingency that is the natural world. Mixed with the mathematical discussions are excerpts from Icelandic sagas, the Bible, and Shakespeare that reinforce the message that our analytical search for meaning is still fundamentally a humanistic endeavor.

If you had to go through it in graduate school you'd probably agree with me that behaviour under uncertainty is usually handled rather mechanically by professors. You may even have considered that, anyway, not much intuition could be behind those theories. Ivar Ekeland shows in this book that dealing with the fundamentals of expectations, probabilities, games, and risk can be fun, and you get the intuition to start thinking by yourself as well. Early morning reading, though.

i find it extremely useful. whenever i looked a term up, i always found it. its easy enough to understand having only a minimum of statistical background, but it is also informative enough to be useful. :) its a winning combination.

This book provides concise, understandable definitions of statistical terms used in medicine and biomedical sciences. Other acronyms and related nonstatistical terms are included, making this work a comprehensive and highly utilitarian reference book for anyone who writes, edits, or attempts to digest biomedical studies. Examples, graphs, and formulas are included when appropriate and necessary, but this book cannot be confused with a medical statistics textbook - it is far too friendly and utilitarian to be confined to use only by statisticians. This is biomedical statistics for the nonstatisticians among us.

Understanding is to understand and from that derive sequences of logical reasoning. While this kind of problem solving books merely stiffens one's (well, at least my) creativity and affects my perception of truth. Not worth reading if you are this kind of people.

It's amazing that so many results that you may have seen in more advanced books proven with more advanced techniques can also be proven with elementary methods. Some of the constructions are amazingly clever. Additionally, the authors take time to highlight the important results in elementary mathematics that are often used in more advanced areas without qualification.

I've read the Russian original of this book. It is wonderful. I really enjoyed it, and often used the ideas I found there to solve other problems. Highly recommended, espesially for the high school students unterested in mathematics, but extremely interesting for anybody who likes math.