Book Description

The goal of this series is to provide readers with a strong foundation in Algebra. Each book is designed to develop readers' critical thinking and problem-solving capabilities and prepare readers for subsequent Algebra courses as well as “service” math courses. Topics are presented in an interesting and inviting format, incorporating real world sourced data and encouraging modeling and problem-solving.Algebra and Problem Solving. Functions, Linear Functions, and Inequalities. Systems of Linear Equations and Inequalities. Polynomials, Polynomial Functions, and Factoring. Rational Expressions, Functions, and Equations. Radicals, Radical Functions, and Rational Exponents. Quadratic Equations and Functions. Exponential and Logarithmic Functions. Conic Sections and Nonlinear Systems of Equations. Polynomial and Rational Functions. Sequences, Probability, and Mathematical Induction.For anyone interested in introductory and intermediate algebra and for the combined introductory and intermediate algebra. ... Read more

Reviews (1)

Blitzer's Intermediate Algebra
Blitzers' step by step is very helpful but does not always use the best path to the solution. He could use more examples of different types of the same problem, ie. What occurs when using negetives on this problem? Great book, but with anything, could be better. ... Read more

Book Description

Fundamental topics and new methods in time series analysis
Analysis of Financial Time Series provides a comprehensive and systematic introduction to financial econometric models and their application to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described.
The author begins with basic characteristics of financial time series data before covering three main topics: analysis and application of univariate financial time series; the return series of multiple assets; and Bayesian inference in finance methods. Timely topics and recent results include:
* Value at Risk (VaR)
* High-frequency financial data analysis
* Markov Chain Monte Carlo (MCMC) methods
* Derivative pricing using jump diffusion with closed-form formulas
* VaR calculation using extreme value theory based on a non-homogeneous two-dimensional Poisson process
* Multivariate volatility models with time-varying correlations
Ideal as a fundamental introduction to time series for MBA students or as a reference for researchers and practitioners in business and finance, Analysis of Financial Time Series offers an in-depth and up-to-date account of these vital methods. ... Read more

Reviews (3)

Analysis of Financial Time Series
This book is awesome. It starts with bedrock concepts needed for analysis of financial data and it takes the student up to the most recent and important techniques used in the industry today. However, if one expects to fully utilize this text, one should have at least one semester of applied econometrics or some equivalent course in statistics and continuous probability, although it will be practical to study the two topics concurrently.

A very practical book
This is not a reference book, and it's not about "big" theory either. It's pretty practical, and good for self study. You should have access to some econometric/statistical software (i.e. EViews, S-Plus, etc.) to fully understand this book.

Petition: please provide table of contents!
I want to see the table of contents of this book. How can the author and the publisher expect people to buy this book without providing the table of the contents?... ... Read more

Book Description

Built from the ground up to meet the needs of today's calculus learners, Calculus was the first book to pair a complete calculus syllabus with the best elements of reform—like extensive verbalization and strong geometric visualization. The Third Edition of this groundbreaking book has been crafted and honed, making it the book of choice for those seeking the best of both worlds. Numerous chapters offer an exciting choice of problem sets and include topics such as functions and graphs, limits and continuity, differentiation, additional applications of the derivative, integration, additional applications of the integral, methods of integration, infinite series, vectors in the plane and in space, vector-valued functions, partial differentiation, multiple integration, introduction to vector analysis, and introduction to differential equations. For individuals in fields related to engineering, science, or mathematics.

Reviews (7)

Very Challenging
Many people say that this book is bad. On the other hand, I think is very challenging. The exercises are not as simple as in other calculus textbooks. The book explains everything well and provides you with many examples. I am a math major and this book has been really helpful.

An excellent book
This is an excellent book for self-studying. I do not understand why some users rate it one star.

Student's Nightmare--AWFUL!
I am an engineering student, and had this text assigned for my Calc 1, 2, and 3 classes. This book was one of the worst mathematical texts I have ever used. The examples were pitiful, and weren't an accurate reflection of the subsequent problem sets. Virtually every section was error-ridden, and the authors' answers were oversimplified, to the point where you would have no clue as to how they were attained.

Also, more about the book itself, and not the content--the binding fell apart for every person that had this class with me, and the ink on the pages will smear with a rub of the finger, or eraser.

The only commendable trait in the text would be the computer-generated graphics/plots. Especially those that were 3D. That is why I decided to bestow the one star...actually, I couldn't give it zero.

If you HAVE to purchase this text for a class, be prepared to write a letter to your professor at the end of the course, telling him/her how awful this text was. If you are looking to purchase it for your leisure reading.....DON'T! There are many better texts out there.

Terrible
This book is one of the worst books that I have bought thus far in college. I am in Calc 3 right now and my opinion keeps getting worse of the book. They should have at least put the correct answers in the back of the book if they were going to put any at all. It's really hard to learn what they confusingly try to teach you, let alone not even know whether your answers are right or not.

Clearly presents a difficult subject
The worst thing a beginning calculus student could be faced with is a dry, confusing text. Bradley and Smith do a good job presenting the material in an understandable fashion. ... Read more

Amazon.com

"Intended as an upper-level undergraduate or introductory graduate text in computer science theory," this book lucidly covers the key concepts and theorems of the theory of computation. The presentation is remarkably clear; for example, the "proof idea," which offers the reader an intuitive feel for how the proof was constructed, accompanies many of the theorems and a proof. Introduction to the Theory of Computation covers the usual topics for this type of text plus it features a solid section on complexity theory--including an entire chapter on space complexity. The final chapter introduces more advanced topics, such as the discussion of complexity classes associated with probabilistic algorithms. ... Read more

Reviews (35)

Life saver
I used this book as a supplement in a college class. It was VERY helpful in understanding computability theory, Turing Machines, and finite languages. Everything is put forth in a straightforward easy to understand manner.

The main thing that made this book stand out above the rest is that it's written in language that is easily understood, while other text books burden you down with a multitude of symbols and equations. The proof ideas are very helpfull in understanding concepts

Thank you Mr. Sipser!

BEST Computer Theory book
This book is by far the best book that I read!!! It presents topics in a very interesting and readable way.

My advice is read this book if you an undergrad student, even though instructor might be using a different book. If you are a grad student this books makes an excellent reference for refreshing your knowledge of Computer Theory. Computer Theory is not my area of interest, but this book makes it very interesting and fun area; which is quiet unusual for Computer Theory books.

I am a grad student taking advanced "Computer Theory" class. I have bought couple books including this one, and checked out from library another 6. This book in an introductory book and it has excellent coverage of the basics, and it has some brief but very good coverage of advanced topics as well. I read this book every time to refresh my knowledge before I go on to more in depth topics. The only thing that I wish, is that the undergrad course that I have taken a number years ago was using this book; and/or I read this book when I was an undergrad.

Probably the best computation theory text for students
In my opinion this is one of the best written books in the CS discipline, a must have for every computer scientist. The topics are presented clearly, with emphasis in understanding the concept, which most of the times is missed in other books amongst the equation line up of theorems that nobody will further investigate. Probably not comprehensive enough for a researcher of the field, but definately the right text to start on the subject and comprehend the basics, which is more than most students in the CS field will need.

A Near Perfect Computer Theory Textbook
This book is suitable for beginners and graduate students who want to explor the theory of computation . It explains the hard theory and logic by easy sentences and words. Even if you use English as foreign language , you can read this book by yourself and understand its contents easily. This book is near perfect.

An EXCELLENT Automata/Theory of Computation book
This book is one of the best written books on Automata/Theory of Computation that I have ever seen. It is a great introduction to the subject. It's also a great way to review the key topics.

One of the greatest things about this book is its focus on developing an intuitive understanding of the concepts and proofs. Other books do a better job of formal proofs but this book is light years ahead of any other in terms of helping you develop an intuitive understanding of why a given proof or construction is correct. It's a lot better than the memorize/regurgitate model necessitated by the emphasis on minutiae of other books.

Lastly, this book provides great tips on how to approach problem solving (especially proofs). ... Read more

Book Description

The Angel Series continues to offer proven pedagogy, sound exercise sets and superior user support. An emphasis on the practical applications of algebra motivates readers and encourages them to see algebra as an important part of their daily lives. The user–friendly writing style uses short, clear sentences and easy–to–understand language, and the outstanding pedagogical program makes the material easy to follow and comprehend. The new editions continue to place a strong emphasis on problem solving. Real Numbers; Solving Linear Equations; Formulas and Applications of Algebra; Graphing Linear Equations; Exponents and Polynomials; Factoring; Rational Expressions and Equations; Functions and Their Graphs; Systems of Linear Equations; Inequities in One and Two Variables; Roots, Radicals, and Complex Numbers; Quadratic Functions; Exponential and Logarithmic Functions; Conic Sections; and Sequence, Series, and the Binominal Theorem. For any professional needing to apply algebra to their work.

Book Description

* Emphasizes the latest trends in the field.
* Includes a new chapter on evolving methods.
* Provides updated or revised material in most of the chapters. ... Read more

Reviews (3)

Cautious and applicable
I'm working with data sets where up to 15% of measurements are unusable. If I'm going to get any results at all, I have to get them despite the lost values.

This book provides a huge library of techniques for working around the holes, as well as techniques for filling them in. This is not a cut-and-paste text for programmers - it gives the basic theory and algorithms for each technique. Still, the presentation is quite readable and fairly easy to put into practice.

The book's emphasis is on imputation - filling in values so that analysis can move forward. This is something to approach with real caution, though. The imputed (synthesized) values must not perturb the analysis, so the imputation must differ according to the analysis being performed. The authors present a variety of imputation techniques, as well as bootstrap, jacknife, and other techniques for measuring the quality of the results.

The authors also dedicate chapters to approaches that work only with available data, and to cases where missing data can not simply be ignored.

This is the most thorough and practical guide I know to handling missing data. In an ideal world, experiments would all produce usable results and surveys would all have every question answered. When you have to deal with reality, though, this is the book.

the bible on missing data
Don Rubin developed much of the current theory on missing data. He and Rod Little have written eloquently on an important and difficult topic. This is the best available reference on missing data. Multiple imputation has been a highly successful technique. It was developed by Rubin and it gets good coverage here. If you are particularly interested in multiple imputation Rubin has another text devoted solely to it. The only drawback to the text is that standard software to handle the new methods was not available in 1987. So there is no coverage of software packages. However, Rubin has worked with Statistical Solutions to get imputation and particularly multiple imputation techniques into a software package called Solas. With Rubin's books and the Solas manual you will be ready to do imputation and more importantly you will understand the modeling assumptions that the methods hinge on.

Classic Text on Missing Data
This is the standard reference for statistics of missing data. Anyone working in the field will find it indispensable. The new edition is updated to cover a number of recent developments in the field. ... Read more

Reviews (15)

Now I get it!
I've just finished studying this book. It's just absolutely delightful. Aftger having taken brain numbing statistics courses in graduate school, this book is like having an expert friend to talk to about the real basis for things. The authors are very thorough in developing baisc statisical theory through examples and practical problems, not to mention interesting and relevant historical background. It's basically a book on learning how to think statistacally, correctly! Common pitfalls togehter with discussions of famous and not so famous goofs and misapplicatinos of statistical methods are throughout the book used (not to poke fun, although it is fun) to develop a second nature in basic concepts. While the book is thick, the reading is easygoing and friendly. It won't take very long for most people to get through it. Concepts are developed progressively on firmly developed and well explained basic ideas. It's as much, if not more, a book on critical thinking as it is on the techniques of elementary statistics. -- Jack Penkethman

Excellent text
I taught an introductory statistics course with this book two years ago. I have to say that *I* learned a great deal preparing for class as I read it--there is a lot of insight and intuition here that you won't generally find anywhere else. Teaching out of it is tough, though, because you don't have the math to hide behind. For those of us used to math, formulas can be a comforting thing. For most students, they're usually just intimidating and the object of many blank stares. IMO, for students who will take only one class in statistics, learning out of this book would be very helpful in a way many other books would not be. For students who will take more than one, gaining a strong conceptual foundation will be helpful as well.

My guess is that the students complaining about this book don't know how good they've got it. You could be stuck with a book that focuses on how to do statistics with Excel or the like, in which case you'll basically learn nothing of subsequent value. :)

Statistics by David Freedman
Useful book. Lots of helpful examples. Don't really need any extra stats resources (like a workbook) if you buy this.

Great Intro Book for Non-Math/Stat Majors
I expected this to be dry and mechanical like lots of other math texts - too-technical proofs, homework questions irrelevant to the material, insufficient explanations for why things are the way they are. This book really surprised me because it wasn't "mathy" at all. It doesn't just throw proofs at you expecting you to wade thru page upon page of math notation until you understand - it gives you the intuitive side of important concepts, which means you only need common sense, not an intensive mathematical background to get everything. The examples they picked simplify rather than confuse the concepts. Each easily and naturally leads to the next. If there's anything not thoroughly elaborated, they were sure to cover it in the homework questions, by gently plodding the reader along towards the answer step by step instead of smacking them in the face with impossible problems. Homework questions supplement the material perfectly and basically leave you with a full and well-rounded impression of what the concepts mean as well as when and why to use them, not just how to plug numbers into some formula.
If anything, I'd say this book errs on the side of caution in that in some sections it could pick up the pace a little. But then again, you could always just skip the easier parts.

Nothing Better -Nothing even comes close
This is not merely the best introductory statistics text, it is in a sense the only one. So far as I know all the others (which were inferior before) have gone "computer." Students are taught how to solve problems on the computer which means they never learn statistics at all.

I have taught introductory statistics for many years and my contempt for the other texts increases year by year. Apparently publishers demand that texts be "computerized" and the authors have been too spineless to resist.

I would like to add that I suspect that most instructors who have used the other texts exclusively would have a tough time with some questions which students of this book would answer with ease. ... Read more

Book Description

This book will appeal to both graduate students and practitioners. Students will value the Excel spreadsheets allowing them to develop their knowledge of modelling in finance, using a step-by-step approach accompanied by explanations using elementary mathematical statistics and probability. Practitioners will value the VBA functions as a source of up-to-date and efficient programs that can be easily used from Excel.

Standard material covered includes:

• portfolio theory and efficient frontiers
• the Capital Asset Pricing Model, beta and variance-covariance matrices
• performance measurement
• the Black-Scholes option pricing formula
• binomial trees for options on equities and bonds
• Monte Carlo simulation
• bond yield-to-maturity, duration and convexity
• term structure models from Vasicek and Cox, Ingersoll and Ross

Book Description

A comprehensive math review for the GRE, GMAT and SAT. This math refresher workbook is designed to clearly and concisely state the basic math rules and principles of arithmetic, algebra, and geometry which a student needs to master.This is accomplished through a series of carefully sequenced practice sets designed to build a student's math skills step-by-step.The workbook emphasizes basic concepts and problem solving skills.Strategies for specific question types on the GRE, GMAT, and SAT are the focus of the Lighthouse Review Self Study programs. ... Read more

Reviews (11)

Great basic math review
The ETS tests you on math that you haven't had in years. This is a great refresher book. Simple, straightforward excercises to get your brain going on arithmetics again. There are 3 parts to the book, arithmetics, algebra and word problems, and geometry. Having reviews all of these parts, I scored much higher on a subsequent practice test. If you can be fluent and fast in all the concepts presented in the book, you should be able to over 650 easily in the quantitative section (plus you should review the GRE Quantitative format).

Really helpful
I hated the idea of tackling math again until I found this little Math Refresher book. The book gave me the easy-to-understand brush-up that I needed and it didn't hurt a bit! For anyone who hasn't tackled math in awhile and who needs an inexpensive jump-start, this book is a great buy.

very intresting one
I haven't deal with math for 5 or 6 years. (BTW: And never loved subject really.) :))) But this book was very good first step in my GMAT math. It's worth it's money and your time if you are starting from "below zero'.

Great for GMAT Prep!
I am horrible at math but needed to brush up for my second shot at the GMAT. This book did an exceptional job of reintroducing math concepts I hadn't seen in years. There were plenty of practice problems with simple and practical explanations.

The first time I took the GMAT, I used Kaplan's math prep book. Although it gave me practice answering GMAT type questions, the reality was I really needed to first was brush up on my math fundamentals.

This book covers arithmatic, algebra, and geometry in 37 lessons. A great buy for anyone taking an ETS test!

A Must Have for Every Family
This book should be stored along side your set of encylopedias and dictionary. ... Read more

Book Description

A modern and highly innovative guide to industrial experimental design

The past two decades have seen major progress in the use of statistically designed experiments for product and process improvement. In this new work, Jeff Wu and Michael Hamada, two highly recognized researchers in the field, introduce some of the newest discoveries in the design and analysis of experiments as well as their applications to system optimization, robustness, and treatment comparisons in the diverse fields of engineering, technology, agriculture, biology, and medicine.

Drawing on examples from their impressive roster of industrial clients (including GM, Ford, AT&T, Lucent Technologies, and Chrysler), Wu and Hamada modernize accepted methodologies, while presenting many cutting-edge topics for the first time in a single, easily accessible source. These include robust parameter design, reliability improvement, analysis of nonnormal data, analysis of experiments with complex aliasing, multilevel designs, minimum aberration designs, and orthogonal arrays. Other features include:

• Coverage of parameter design for system improvement first introduced by Taguchi in the mid-1980s
• An innovative approach to the treatment of design tables
• A discussion of new computing techniques, including graphical methods, generalized linear models, and Bayesian computing via Gibbs samplers
• Each chapter motivated by a real experiment
• Extensive case studies, including goals, data, and experimental plans
• More than 80 data sets as well as hundreds of charts, tables, and figures
... Read more

Reviews (4)

A Superb Graduate Textbook
There are many ways one can judge a textbook. For graduate textbooks, the most important aspect one should look at is if they are worth keeping. Taking a graduate course in statistics generally means that one has chosen a career in statistics or a career with a significant statistical component in it. So the value of a textbook after graduate studies is an important consideration any instructor should give. It is pitiful that some of the textbooks from my own graduate studies are not worth a second reading, either because they lack modern topics or because they are mostly devoted to mechanical derivations.

Wu and Hamada (2000) is a superb textbook in this regard. The book is loaded with a number of most important modern topics in design of experiments, including robust parameter design, minimum aberration, designs with complex aliasing, and generalized linear models (p. xvii). These modern topics only receive some courteous treatment, if any at all, in most of design textbooks. The importance of these topics cannot be over-stated. It is impossible for an instructor to provide a detailed coverage of all the important topics in any design course. Practical problems often require the use of certain methods, which may or may not be touched in a design course. Therefore, we will often have to go back to our graduate textbooks to do some further reading. The comprehensive design tables in Wu and Hamada (2000)
also make this further learning process easier. For those who are doing research in the area after their graduate studies, Wu and Hamada (2000) is a necessity. Accessing design literature through journals is much more inconvenient and time-consuming. Wu and Hamada (2000) is also a suitable textbook for a design course for undergraduates majoring in statistics, or other areas of mathematical sciences.

If I can only own one design book, this is the one.

Not in touch with Grad Students...
I think this book has great potential. Unfortunately, it suffers from a few of the most fairly common Graduate Level text book problems.

Use of the 'et cetera' function, or a failure to work out examples. I'm not sure if I'm in a minority with this opinion, but I believe, after many years as a graduate student that examples should be worked on in their entirety. Unfortunately, this in not the case with this textbook. There are numerous places in this text where the authors reference, with great generality, pervious half-worked examples or formulas. Not only does this make the text sometimes difficult to follow, it also reduces the usefulness of the book as a self teaching tool.

The text also fails to include even some of the solutions to its exercises. I'm not sure why many authors fail to include even some of the solutions to their chapter exercises. In my opinion, I believe that this is a serious weakness in text. Most professors who teach graduate level courses create their own problem sets. By failing to include even partial solution sets, the authors minimizes or completely destroys any benefit of including exercises in the text (especially if you are not reading this text as part of a course). There is no benefit of working out exercises if you can not correct or even identify your mistakes.

If I had to have just one "Design of Experiments" book, I would not choose this one. Although there are many great things about this book, it is notoriously light on Split-Plot experiments. In fact, Split-plot experiments (which are very common) only receive a cursory mention. If you are looking for Books on Designs of experiments, I suggest you look at "Design and Analysis of Experiments" by Douglas Montgomery, or maybe even the older "Statistical Design and Analysis of Experiments" by Mason, Gunst, and Hess.

authoritative and thorough treatment
Jeff Wu got his Ph.D. in statistics from UC Berkeley. He started his career at the University of Wisconsin in Madison where he was influenced by George Box and was exposed to many important practical design problems. Jeff quickly established himself as a top notch theoretical statistician publishing some landmark papers in the Annals of Statistics. As his career developed at Wisconsin and later in Canada and at Michigan he made fundamental contributions to survey sampling and experimental design. This book is basically a sequel to the classic book by Box, Hunter and Hunter. It includes all aspects of experimental design and is very thorough in covering all the classical topics and the new area of robust design. It includes many recent advances by the authors (Wu and Hamada) in the 1990 and even the late 1990s (papers from 1997 and 1998 are referenced).

The book is intended for scientists and engineers as well as statisticians. The authors deliberately introduce the concepts gently, starting with a real problem and constructing and analyzing a design type considered in the chapter. This is done consistently from chapters 3-13.

They start with the simplest ideas and designs and build up. Chapter 1 deals with single factor experiments and Chapter 2 with experiments with more than one factor, starting with two. Section 1.1 provides an historical perspective which I find valuable. It leads to a classification of design problems that are distinct and they show how they arose in very different contexts. They do a good job of setting the stage for the remaining chapters. The categories are (1)Treatment Comparisons (the traditional agricultural experiment), (2) Variable Screening, (3) Response Surface Exploration, (4) System Optimization and (5) System Robustness. Although the theory of optimal designs is not covered in detail, the role of optimal designs is mentioned as is the early work of Kiefer (section 4.4.2)and reference to the recent book by Pukelsheim is given.

In Chapter 4 on fractional factorial experiments at two levels, concepts of resolution and aberration are clearly explained. I think it helps that the authors make these concepts concrete through the illustrative examples. I have often looked at standard design texts and found myself confused about the distinction between resolution III, IV and V designs.

There are several features that set this book apart from other books on design of experiments. Some attention is given to the one-factor-at-a-time approach. Most books ignore this commonly used approach and its many drawbacks. The authors explain its four main disadvantages and illustrate the problem with a design example. In my experience in industry, many engineers are not trained well in statistics and although it may seem clear to statisticians that one-at-a-time approaches overlook interactions or dependencies between variables, the engineers often do not. They see this approach as a way to simplify their search for the best operating conditions. I published an article in the mathematical modeling literature that also was intended to demonstrate the value of statistical design methods over the one-at-a-time approach. Latin square and Graeco-Latin Squares are covered as well as the more common factorial and fractional factorial designs. They also cover randomized blocks and balanced incomplete blocks. The concept of pairing (blocking) is well illustrated with a particular analysis of variance done both with and without pairing. Underlying assumptions are brought out and never hidden. The principles that are the basis for selection of fractional factorial designs are made explcit. Practical nonregular designs including the popular Plackett-Burman designs are well covered. Chapter 10 provides the basis and motivation for robust parameter designs. It also includes a discussion of the signal-to-noise ratio approach of Taguchi and describes some of its weaknesses. Chapter 11 looks at various performance measures for robust parameter design and compares several designs with respect to these parameters.

In the early chapters, the analysis of variance is presented clearly with all the required assumptions. Multiple comparison methods are discussed. Good references, both recent and old, are provided on each topic. My only disappointment was the omission of the recent resampling approaches to p-value adjustment due primarily to Westfall and Young.

Another interesting and unique aspect of the book is the presentation of Bayesian variable selection strategies. This introduces much of the interesting new work in Bayesian methods using the Markov Chain Monte Carlo methods.

Chapters 12 and 13 cover topics you will not find in other experimental design books. Chapter 12 deals with experiments to improve reliability and 13 with nonnormal data. Use of generalized linear models and transformation of variables is well covered in the book.

This book is a worthy sequel to Box, Hunter and Hunter. It is a great introductory book for experimental design courses and a great reference source for scientists, engineers and statisticians. It is already gaining in popularity.

A classic book on experimental design
This book is on the par with Box, Hunter, Hunter's famous book "Statistics for Experiments". If you already have the latter one, you should have both.

This book devotes more than half of its chapters to cover the rapid new developement in past two decades that was not ready to be coverd by BHH back in 1978.

First four chapters cover the same classic designs in BHH. Chapter 5 discusses in detail on three level factorial designs which is very useful but was not covered by BHH. Chapter 6 lists useful mixed level designs. Chapters 7 and 8 explain design and analysis of Platt-Burman and other irregular designs. Chapter 9 is on response surface design. Chapters 10 and 11 are devoted to Robust designs, better known as Taguchi method. Chapter 12 is specific on reliability study using experimental design. Chapter 13 wraps up the book with a nice discussion on how to deal with non-normal responses in an experiment.

The book is full of data from real experiments. There are on average 7-8 in each chapter. For practioners, there are hundreds of designs tabled after each chapter.

The authors explain the strategy of designing experiments and doing data analysis very clearly through examples. There are also pletty of exercise problems after each chapter. It could be used as a textbook for two semester experimental design courses.

The authors did not try to cover everything but rather stay focused. For example, optimal designs are left out from the book. Most of the data analysis method in the book requires to be done using statistics softwares but you couldn't find a single computer command in the book. Maybe in the future, we will have SAS books, S+ books, and Minitab books to go along with this book. At this moment, the software developers have to catch on. ... Read more

Book Description

The fourth edition of Probability, Random Variables and Stochastic Processes has been updated significantly from the previous edition, and it now includes co-author S. Unnikrishna Pillai of Polytechnic University. The book is intended for a senior/graduate level course in probability and is aimed at students in electrical engineering, math, and physics departments. The authors' approach is to develop the subject of probability theory and stochastic processes as a deductive discipline and to illustrate the theory with basic applications of engineering interest. Approximately 1/3 of the text is new material--this material maintains the style and spirit of previous editions. In order to bridge the gap between concepts and applications, a number of additional examples have been added for further clarity, as well as several new topics. ... Read more

Reviews (19)

Papoulis is Useful
I first encountered the works of Papoulis when just out of graduate school in pure math, and worked for a major defense contractor as an analyst. I found out that almost all the engineers there had this book, and purchased a copy. I had studied stochastic processes at a much more theoretical level than is presented in this book, and that study was significantly more difficult than the material in the text under review, so complainers take note. Why do I think this book an excellent one? Because it is so eminently USEFUL to the working engineer. I believe that has been the intent of the author in all of his works. If you're a working engineer who needs to find answers to tough problems, you can scarcely do better than to consult Papoulis.
For example, the material on power spectra is of more than academic interest and is useful in applications; the bivariate Taylor expansion for moments of a function of two distributions has been used again and again in applications in industry; especially in the analysis of the ratio of noisy variables arising from radar measurements. The point is that the text provides the material in a readily accessible way for someone who needs it in the "real world" of engineering analysis.

Too elementary
This book lacks rigor, and contains horrendous typos (but there is an errata sheet available) although makes a nice effort to "engineerize" the topic for the dumb reader (i.e. engineers).
Not meant for the mathematician, it makes no use of measure theory, and so you have to believe the results at face value.
On the positive side, it contains tons of worked-out examples, the chapters on distribution functions are quite nice and contain nice applications of calculus.
Other than that, it is a bit too elementary and avoids any of the interesting topics dealt with in more rigorous courses such as the stochastic integrals.

Did I already mention this is an easy book? I don't see why the other reviewers complain it is hard, it must be due to their low IQ, so I wouldn't worry about their comments too much. These engineers want the answer ready to copy down on their homework sheets, this book almost gives you the answer if you're able to do changes variables etc., although this is sometime a difficult task for freshman engineers.

Not easy but worth the effort
This is a book which definitely requires diligence and effort to get through. The excercises are also not trivial to say the least. However, if you have the energy and patience to actually slug through this text, in the end you will discover that you have actually learned something. Something which is profound and difficult to understand. This book is definitely not recommended as a casual reference.

Not a good textbook
IMO, this is not a good textbook. On one hand, it never explains the purpose of the materials. I know it elaborates on the random variables and different distributions and a lot of materials in detail, but I don't know where can I use these things. On the other hand, it omits the mathematical details, too. So when I read this book, I found unclear points everywhere. Someone else recommended this book as a good engineer reference. I think that might be true if there were less errors. I find errors in the equations every two or three pages. Engineers may not need to know the details, and they know what they need to model their designs. But they need the "correct" thing to do that. Maybe that is not the author's fault but McGraw-Hill's, but to me, a reader of the textbook, it is the same. No recommendation of this book.

Plenty Of Examples. Great Detail
This book has a huge pool of examples that enables the reader to understand the concept better. The subject itself is "NOT TRIVIAL", however if it wasn't for this book, it could have been worse. I own this book and I liked it. The examples are fairly easy to understand and relevant to the end of chapter problems. There is also a web site for this book that has a lot of additional resources. So if you are thinking of buying this book, then go for it. (Please Note that I am writing this review for the Fourth Edition Hardcover by Papoulis and Pillai. Previous edition is not that good) ... Read more

Book Description

Reviews (1)

Useful, but need solid background in stats
This book describes important advances in statistical analysis of social science data, circa 1992. Much of this data has a natural hierarchical grouping. But traditional statistical methods proved inadequate at coping. The biggest drawback was the failure of the assumption of independence. If at the lowest level, Items I1,...,In are grouped into sets J1,...,Jm, where mTo handle this, Hierarchical Linear Models were developed. The book gives a detailed treatment. A very comprehensive discussion. Including the handling of meta-analysis, where we wish to combine results across different studies. Which then involves using empirical Bayesian estimates. This method has also seen important usage in evaluating medical studies, conducted by different researchers on the same topic.

The book also illustrates the essential development of non-trivial computer programs to perform the gruntwork.

You will need a solid background in statistics to find this book useful. At a minimum, a year of statistics at the undergraduate level. ... Read more

Reviews (1)

very nicely done!
I've just started working with this book, but I'm very impressed. Very clear layout, has lots of examples and exercises (with answers to even numbered ones). Very good about explaining why things are done a certain way, and especially strong in asking questions a typical reader might have. I'm recommending this for my graduate course on research methods for information technology. ... Read more

Book Description

This is the most widely used mathematical statistics text at the top 200 universities in the United States. Premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid undergraduate foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps students discover the nature of statistics and understand its essential role in scientific research. ... Read more

Reviews (8)

Solid Presentation But Lacking Concision
The sixth edition of Math. Statistics w/ Applications is a solid book with good information. However, the form of presentation was not for me. The authors have chosen an explicative style which tends to be overly wordy.

When I begin to read a chapter, I tend to get frustrated and impatient because they either try to show you all the subtleties at once or give you a long-ass paragraph that can be said with one sentence. Thus, The most important stuff is buried in a mountain of over-whelming text.

I have ditched this book in favor of Ghahramani's "Fundamentals of Probability, Second Edition" for my Math Stat I class.

Best statistics book for econometricians
This book is a book on mathematical statistics and hence goes further than most entry-level statistics books, which mostly deal with business statistics. This book does not reinvent the wheel, but is goes further where other books end. You will find a mathematical explanation and theorems are proved as well. Soms more advanced topics are moment generating functions and power tests. The consequention is that the learning curve is steeper. At my university, econometrics students use this book, and they couldn't have made a better choice. Logically, since econometricians don't have enough on a book with only a minor focus on formulas.

Worst stat book ever
I work as an actuary, and I have passed the first actuarial exam (the calculus and stat exam with a <30% pass ratio). My friend uses this book for her stat class, and I have found it to be a terrible book.

I hope that any teacher reads this, and looks at the book before assigning it to a class.

There are very few examples of problems, very little discussion of theory, and it is structured in a way that does not allow you to easily reference other texts.

If you want a good text for challenging problems and relevant examples, try Hogg and Tanis.

A great book!
This is definitely one of the best introductory statistical books around. The writing is lucid and masterly, and includes a wide variety of topics. The authors have included an abundant number of well-chosen exercises and these cover a wide spectrum showing the application of statistics to the engineering, biological, etc., sciences. My only complaints are that there is not enough on residuals and influence in the chapter on regression; the use of the hat matrix in this context would have been most beneficial, in my opinion. Also I would have very much liked to see the Fisher information in inference and the Smith-Satterthwaite procedure in hypothesis testing included. Nonethless both students and instructors will find the book extremely useful and it gets my highest recommendations!

Three standard deviations from the mean...
As a student in Engineering Science at the University of Toronto who used "Introduction to Mathematical Statistics" by Rice as a textbook for a course on Probability and Statistics, I must say that my life would have been so much easier had I owned a copy of Wackerly's text. It is a concise, easy to follow, practical textbook that covers the material thoroughly while still presenting it in a most digestible form. ... Read more

Reviews (1)

Easy - Simple - Plain
The problems given in this book were very easy to understand. The author shows step by step how to do the given problems and the answers are refferenced in the back. I always used how the book did the problems, not the teacher's way. I am always coming back to this book to refresh my math skills. ... Read more

Book Description

A Brief History of Time, published in 1988, was a landmark volume in science writing and in world-wide acclaim and popularity, with more than 9 million copies in print globally. The original edition was on the cutting edge of what was then known about the origins and nature of the universe. But the ensuing years have seen extraordinary advances in the technology of observing both the micro- and the macrocosmic world--observations that have confirmed many of Hawking's theoretical predictions in the first edition of his book.

Now a decade later, this edition updates the chapters throughout to document those advances, and also includes an entirely new chapter on Wormholes and Time Travel and a new introduction. It make vividly clear why A Brief History of Time has transformed our view of the universe. ... Read more

Reviews (281)

A classical predecessor of the Elegant Universe
Stephen Hawking is the first physicist who was able to combine the laws of the small - quantum mechanics - with the laws of the large - general relativity - to find out something fascinating: black holes evaporate. He was also the first man who published a book on theoretical physics that has become popular world-wide (about 9 million copies have been sold). Many readers have learned a lot of exciting things about our universe from this book. So did I - even though I was a student of theoretical physics. Although this book is not as perfect as Brian Greene's "The Elegant Universe", the successor of the Hawking's book in the position of the book on theoretical physics causing such a stir, "A Brief History of Time" will remain a tour de force, a pioneering work which began a new interest in physics among masses of people. That is why do I recommend you to read this book about the big bang, black holes, the quest for the ultimate theory and many other issues.

Scientific Literacy
In the modern era, natural science is more than a lot of abstract thoughts and boring jargon--it is a leader of society. Newton's theory of physics, Darwin's theory of evolution, Heisenberg's uncertainty principle--all have changed the way we think about the world, influenced other disciplines, and ultimately changed society.

Because of this profound effect science has on society, it is important for the general public to understand the ideas and development of science. Unfortunately, it becomes increasingly difficult to do so as science becomes more specialized and technical.

Enter Stephen Hawking and 'A Brief History of Time.' The book is one of many great books that increase scientific literacy for ordinary people like me.

Only someone who fully understands the basic concepts of theoretical physics could put it into clear and easy prose as Hawking does. He outlines the progress of theoretical physics and the theories that attempt to describe the universe, all in plain English.

Hawking paints a picture of the universe--its beginning, its end, the direction of time, black holes-- with the wonder and curiosity of the child plus the style and confidence of a brilliant mind. One of the most brilliant minds in this century, as a matter of fact.

The final sentence about knowing the mind of God--"the ultimate triumph of human reason"--reminded me of that timeless scene in the Bible where the serpent convinces Adam and Eve to eat the apple.

Figuratively (*figuratively*) , that triumph is what we left Eden for. We have left Paradise for unknown horizons, for questions instead of answers, for a world of wonders. That quest is what A Brief History of Time is about. Do yourself a favor and read this book.

a marvel of a book
This book is truly a gem.. small volume but packed with a density of information..
Explore fascinating topics you could not think about in your wildest DREAMS.. topics are Black holes, Entropy, Origins of universe, Time Travel.

Hawkings is truly a genius among geniuses.
(...) If you can finish the book, the knowledge is well worth it.

Excellent Introduction for the Curious Mind
For anybody who does not have sufficient knowledge to read some of Hawking's more complex writings, this is the perfect book to get started on. It introduces you to the concepts of astrophysics, in which are explained very well. Stephen Hawking uses humor and everyday scenarios to explain some difficult concepts of astrophysics. It is a great way to simply expand your knowledge by understanding the big bang, quantum mechanics, and even sub-atomic particles. Stephen Hawking is an excellent writer, not to mention the Albert Einstein of our time; he makes this book almost seem like a novel more than a non-fiction book. I highly recommend this book to pretty much anyone, because it introduces you to astrophysics, as well as just answering questions regarding time travel, or where we came from.

Hawking is succinct, even-handed, and even funny.
A Brief History of Time is 3 things at once:

First, it is a chronology of the various important scientists and discoveries over the centuries, all leading to where we are now.

Second, it explains, between the beginner and intermediate levels, an understanding of concepts such as black holes, worm holes, the beginning and potential end of time, particles and waves, quantum mechanics, and other issues in science.

Third, it is almost an autobiography of Dr. Hawking's scientific life. He interjects wonderful bits of humor and explains the concepts carefully and as simply as he can.

He is also respectful of religion, briefly interjecting his ideas about how religion does not have to be incompatible with the rapidly expanding ideas of science, and that religion should embrace science more.

One part I found humorous was his explanation of a bet he lost with a colleague (he seems to have a lot of long-standing bets going). He owned up to being wrong, and paid the penalty, which was a "one-year subscription to Penthouse, to the outrage of [his colleague's] liberated wife."

This book is for physics experts as well as people who know nothing about science and just want to learn some of the basic concepts. Like the universe, expand your mind. ... Read more

Book Description

This best-selling book provides an accessible introduction to discretemathematics through an algorithmic approach that focuses on problem-solving techniques. This edition has the techniques of proofs woven into the text as a running theme and each chapter has the problem-solving corner. The text provides complete coverage of: Logic and Proofs; Algorithms; Counting Methods and the Pigeonhole Principle; Recurrence Relations; Graph Theory; Trees; Network Models; Boolean Algebra and Combinatorial Circuits; Automata, Grammars, and Languages; Computational Geometry. For individuals interested in mastering introductory discrete mathematics. ... Read more

Reviews (33)

Par Exposition and Expensive
I used this book for a one semester course on discrete mathematics. First for the bad points: This book is unnecessarily expensive. 1/3 of almost every page is left blank and has unnecessary text and pictures. If there is one thing a poor college student doesn't need is an expensive book. I've read through the majority of the reviews here. Most of them stress that the book is difficult to follow. Indeed, some proofs and examples are difficult to follow (unless you have the intuition of a genius). The author's exposition of the material is not bad, but not good either.

I'm currently trying to solve some of the more interesting problems in the book from each chapter. I must say though, some problems are INCREDIBLY challenging. I've been through many instances where I've required outside help to solve some problems.

Conclusion: I don't recommend buying this book. It's too expensive and its exposition of the subject is