Product Description
In their bestselling MATHEMATICAL STATISTICS WITH APPLICATIONS, premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid 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 you discover the nature of statistics and understand its essential role in scientific research. ... Read more

Customer Reviews (37)

Very Good
The shipment was just on time and the book was really good too. I have no complaints what so ever! Thanks a lot!!

Outstanding book, Kindle edition marred by problems
I've read a lot of statistics books, and most of them are poorly written. Their explanations are limited and often obscure. Their assumptions often go un-mentioned. That applies both to lower-level "statistical methods" books and higher-level theoretical books about mathematical statistics.

This book stands far above the pack. It explains concepts and techniques clearly, completely, and with all the steps included. I wish that I had started with this book instead of struggling, painfully and at great length, with the others.

One problem: I've been reading this book in the Kindle software for my iPod Touch. In the Kindle edition, some parts of the text are missing: not whole pages, but a paragraph or two here and there. Because I don't have the printed book (though I might spend the extra money to buy the printed version, too: this book is that good), I can't be sure if the omissions are just a problem in the Kindle edition. However, it seems like a reasonable assumption.

I would give this book a full five stars except for the problems in the Kindle edition. It's outstanding. I want to marry this book. :-)

Quality Textbook
I have only been through a few of the sections, but the writing is clear and accessible. As the authors state in the introduction, statistics is treated as a branch of science, not as a branch of mathematics (paraphrase). This perspective is the same as my own, and the book has been very helpful.

Badly written textbook on easy contents
After reading through this book and couple of other math stat text like Larsen and Marx, DeGroot, and Berger, etc, this is what I find:

1) The content is shallow.No rigor to mention of.Many proofs are not offered.Proofs offered are always very informal.

2) The authors make easy content overly complex by stating things in many different way, as if this helps learning.

3) The authors absolutely hate "X."They use Y1 and Y2 instead of X and Y, which I think is a much more straightforward and easy notation.So you get the idea, there are subscript to subscript, when in fact the author can use X and Y to avoid additional level of subscript.I read all other textbooks, and this is the only one which uses y1 and y2.That means, if your instructor sucks, you are out of luck, because you cannot reconcile notational difference without investing a lot of library hours.Maybe the author is trying to make students accustom to their notation, so students cannot switch!

4) The author explains easy concepts in details, but skimp through different concepts.That is sad: because students end up waste a lot of their time reading what is apparent or easy to understand, but still don't know the difficult concepts such as mgf and inner workings of gamma functions.I use Berger's Stat Inference textbook as a helper for this textbook!

This book claim it is the most popular; well I say the sales team must be awesome. This is a bad textbook.

virtually worthless
The examples are insufficient and do not show what formulas the results are derived from or the mathematical or statistical steps that are needed. The proofs also do not tell you the necessary formulas and often tell you to refer to sections that tell you to refer to other sections. Worst of all are the problems, which do not give you any hints and so you won't know if you are doing them with a completely wrong method. The book also does not give some of the necessary formulas to solve many forms of the problems. The distributions and estimators that you will need to work with are usually not given. If your class requires this book, you are going to be pulling your hair out in frustration and you'll need significant amounts of help for about half of the problems. ... Read more

Customer Reviews (3)

only has odd numbered problems
all the problems in it are worked out really well, but it only has odd numbered problems, just like the back of the corresponding textbook

great detailed answers!
for all the odd problems, it gives a very detailed answer!as long as you know ahead of time that you're not getting answers for the even problems, you won't be disappointed!a great companion to the text!

Unnecessary
The solutions manual contains answers only for the odd problems, which is what the textbook contains in the back sections. So why did I buy the solutions manual? GENIUS ... ... Read more

Product Description
This is the first text in a generation to re-examine the purpose of the mathematical statistics course. The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts that are set in abstract settings. ... Read more

Customer Reviews (49)

A valuable reference for empirical modelers
My learning in statistics follows a funny order. Before receiving fundamental training in math stat, I took an introductory stochastic processes and graduate econometrics. I use Rice's book for a math stat course this summer and find this book a valuable reference!

This book helps me synthesize what I've learnt from stochastic processes and economoetrics. On top of that, it provides very useful techniques that will assitempirical modelers to perform estimation of probability models and dereviation of random variables. This book is not advanced enough for stat PhD students but definitely a must-read for non-stat majors who want to get a deep understanding of statistical sciences.

I personally obtain ideas from this book to solve problems confronted in model-development and data-manipulation.

The only thing I would complain about this book is its price.

Decent book but not for biological sciences
This book provides a decent review of basic statistical concepts with application examples.The strengths of the book are that it has a good background chapter on probability, provides some information on non-parametrics, and is firmly rooted in mathematics (ie proofs are offered to demonstrate how some formulas are obtained).Weaknesses of the book include an odd narrative (not typical for a textbook), poorly organized chapters, and inadequate coverage of some topics (ANOVA, MANOVA, ANCOVA, normality tests, K-S test, etc.).I do not recommend this book for anyone in the biological sciences because it does not adequately cover the most used "advanced" tests.

Bought out of compulsion
I had to buy this book just because my teacher used it as required text. The book is pretty mediocre, clearly not worth $135. You can get much better understanding of statistics using books by Schaums series. The book does have decent examples, but is very overpriced- I do not believe it should cost more than $20.

A good introduction, good reference
This is one of the most readable mathematical statistics textbooks. The level of math used is just right for this course. You need to use is mostly univariate calculus, but partial derivatives may pop up in a few places. You also need to know matrix algebra to read most of the chapter on linear models. All derivations and explanations are clear. The statistics portion of the text starts with sampling theory. In fact, it has more on sampling than I personally wanted to learn, such as sampling from finite populations and stratified sampling. Then it continues with estimation methods and hypothesis testing. There is a very good chapter on descriptive statistics. The later chapters focus on specific models, such as comparing the means of two samples, analysis of variance, categorical analysis,and finally the linear regression. The first chapters summarize probability theory, so the text is very much self-contained even for those with no probability background. There is also a chapter on Bayesian methods, which I haven't read.

The two features that I personally like in this text is that for some models the author presents such modern and sophisticated topics like non-parametric statistical techniques and bootstrap methods for obtaining standard errors. Overall, this is a fine textbook. It gives a solid introduction to statistics for people who need to do statistical analysis on their own and for whom this is their first and last statistics course. This text also gives a nice introduction for students of statistics who plan to move onto more advanced texts. There are one or two places where the derivation is simple but gets a little daunting (I think one of them is one of Wilcoxon's tests). But in the end, you must accept one fact. This is a serious university level applied math text for sophomores/juniors. This book can't be read like a novel, though it is a very readable text as far as mathematical stats goes.

Ignore most of those negative comments from readers many of whom clearly have not mastered their calculus and probability skills before taking a stats course. Undergraduate mathematical statistics is a kind of a course that attracts lots of people from many different majors and math backgrounds. Some take stats only because they have to, not because they want to. In the end, (this may sound arrogant), but the quality and motivation of students in an undergraduate mathematical statistics courses may be very variable. Some probably do not belong in a serious stats course. Hence, the flood of negative reviews for this text.

Dont waste your money and this book is really confusing
if you have choice, dont buy this book, it just waste your money and it will totally confuse you. you wont understand the concept through this book. unclear definition, useless example, if you have to use this textbook, you have better have time to search statistic information online by yourself. i am currently suffering from this book, since it is written by a professor in our school. i dont think he knows students well, the book is so unclear and confusing :( ... Read more

Product Description
This classic book retains its outstanding ongoing features and continues to provide readers with excellent background material necessary for a successful understanding of mathematical statistics.Chapter topics cover classical statistical inference procedures in estimation and testing, and an in-depth treatment of sufficiency and testing theory—including uniformly most powerful tests and likelihood ratios. Many illustrative examples and exercises enhance the presentation of material throughout the book.For a more complete understanding of mathematical statistics. ... Read more

Customer Reviews (43)

A Strong Standard text, but the binding is flimsy
This is a strong standard text in statistics that I am currently using to teach from in a senior level course for math majors.The coverage of the material is solid and the assortment of problems is excellent.Unfortunately, it currently only seems to be available in paperback and the quality of the binding is very poor.Students in my class who bought used hardcover copies had no troubles, but most of my students who bought new paper bound copies have had the binding crack and pages begin to fall out.

Too abstract for the student without some experience in analysis
It covers most of the introductory topics in mathematical statistics but reading and understanding from the book without some help from the instructor is extremely difficult. If you can get the help from your instructor, its the ideal book to learn the material. By the way, the soft cover sold on Amazon will fall apart in a couple of weeks, buy the hardcover somewhere else if possible. It costs the same.
Similar book worth checking out is Statistical Inference by Casella and Berger.

Required Text
This text is required reading in the City College of New York Mathematics Course: Statistics I.Familiarize yourself with Linear Algebra, Multi Dimensional Calculus before reading.If you haven't taken Probability theory then you may have a difficult time but the author does an excellent job of re-introducing the concepts of Set Theory, Distributions, and Probability Space in the first two chapters.

***DO NOT*** BY PAPERBACK VERSION!!
I have no problem with the content of this book.The problem is with the book itself.I got my order in very fast from amazon, but immediately (and I mean within hours) the pages started falling out.I'm not one to complain about the quality of books, but this book is clearly poorly made.I have a classmate who bought the same paperback and I laughed because the first question he asked me was if my pages were falling out.Buyer Beware!

My Favorite Intro Mathematical Stats book
But my sample is small (2). I used this book as a math undergrad. After some time off I'm working on my masters in statistics, we're using Statistical Inference by Casella and Berger. The books cover the same material, but I find the Hogg-Craig explanations to be much clearer.

I also used this book to study and pass the first actuarial exam, along with test prep material. ... Read more

Product Description

This graduate textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. degree in statistics. This new edition has been revised and updated and in this fourth printing, errors have been ironed out. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are useful in statistics. The second chapter introduces some fundamental concepts in statistical decision theory and inference. Subsequent chapters contain detailed studies on some important topics: unbiased estimation, parametric estimation, nonparametric estimation, hypothesis testing, and confidence sets. A large number of exercises in each chapter provide not only practice problems for students, but also many additional results.

Customer Reviews (10)

I have not got the book yet
I purchased two books. One arrived quickly whereas the other did not reach my hand yet. Why? And there is no track to follow too.

Has everything you need, if you can read and understand it.
I don't know if statistics are just that difficult a subject or statistics writers just aren't good.Either way I have not found a satisfactory statistics book that treats the subject rigorously, but still readable.This book is an excellent reference.However, it's notation is cumbersome, if you're not used to it.

Before I started taking the class that uses this book, I took four undergraduate probability and statistics classes, as well as studied advanced topics such as measure theory.That said many of the things in statistics I thought I understood, I found out that I do not, or had a hard time translating my undergraduate knowledge to this level.As with many advanced math subjects, the definitions are not enlightening and no motivation or further discussion is given for most definitions.These definitions are designed to fit into as general theory as possible, but trying to understand why some things are defined the way they were, and what the original intent of the object was, is just not there.

To use this book, you will definitely need the guidance of an expert statistician.

Good reference
This book, coupled with its accompanying exercises volume is a good source for beginning graduate level statistics.

Excellent, very clear, accurate notations
Update: In 2010 I am using this book again to review probability and statistics in preparation for applying to a PhD program in Finance or Risk Management.I still find the book to be extremely clear. Everything still seems up to date, surprisingly. I like that fact this book has a longer useful life than an iPod or a cell phone, but is a LOT cheaper :-). The sections are very concise, sometimes just 2-3 pages, so this is definitely a reference book and not a learning book. I think it's most useful for a quick comparison of the different methods for someone who has already learned most of the material before.
---------------
I know it must be a sign of extreme geekyness to be reviewing statistics books... but it happens to be one of my passions. (So that proves it takes all kinds of people to make the world go around.) I find this book to be unusually clear.Printing is also of high quality and I did not spot sloppy notation errors.I would judge the level to be about first or second year PhD level. First chapter lays out probability theory very well and introduces the more standard notations. I find books that use the less standard notations to be annoying. I got this book to use as a reference book rather than as a textbook.I wanted to have a concise place to look up and compare the different methods.If you are learning this material for the first time, I strongly suggest you take at least one applied statistics course first. I don't think one can learn statistics easily without using data and actually running the models. Also this is definitly a graduate level book.I don't think it will be a good idea to try it before reading through several undergradute-level books on probability, regression, and statistics.

For more descriptive graduate-level books in econometric, "The Practice of Econometrics" by Ernst R. Berndt is good for hands on practice.Kennedy's "A Guide to Econometrics" provides a descriptive explanation of the various models.

Great book, not for kids
Don't waste your time: this is a rigorous book on mathematical statistics, done right, for mathematically mature readers.

If you want a plug and chug manual, buy something else. If you want precision and rigor, buy this. ... Read more

Product Description
This classic, calculus-based introduction to the theory and application of statistics provides an unusually comprehensive depth and breadth of coverage and reflects the latest in statistical thinking and current practices.New to this edition is the addition of an applications section at the end of each chapter that deals with the theory presented. Further emphasis has been placed on the use of computers in performing statistical calculations. Topics covered include probability distributions and densities, random variables, sampling distributions, hypothesis testing, regression and correlation, variance, and more.An excellent reference work for professional statisticians in a variety of fields. ... Read more

Customer Reviews (15)

terrible book
I am using this textbook in an undergraduate class on mathematical statistics. The book has many misspelling even at places where comprehension could be jeopardized. Many exercises tells you to refer to previous exercises which you may not have already solved. In general it is annoying that the book has too many references to previous results that are not even that important; you have to do a lot of page flipping. The textbook could have benefited from providing more examples as usually the examples after a section don't cover all that is discussed. Important results do not stand out enough for easy access and sometimes there are hidden parameters buried in the text before a theorem. There really is nothing special about this book. All problems are pretty straightforward computations. The text avoids proving how a result is derived when it is beyond the level of the text. This makes it seem like I am just plugging in formulas rather than understanding the theory. At this level, there should be better books out there. Considering how basic the book is, the price alone should dissuade you from buying it.

Thanks a lot
I need to thank this supplier becasue I had failed three times when I tried to buy this book online.
It was shipped fast and delivered fast. Appreciate it.

Not enough Pictures
Yes, even at the collegiate level, pictures are needed.The example problems rarely drew the diagrams/pictures.Also many of the problems refer back to previous examples in different chapters.For example, a problem in Ch 7 has us take the information for a problem in chapter 3; without a corresponding page number.Also the lay out of book is very compact.I wish the authors did not squeeze so much information on one page.The could have used more space, showed much more algebra steps, and MORE DIAGRAMS.

Avoid
I'm taking a course in statistics as an independent study using this book.It might have been better had I been taking a class with a professor helping me understand the problems, but trying to understand with just this book is next to impossible.The examples skip steps, which I suppose I am just suppose to know, with no explanation or note that there have been operations omitted.This is very confusing.I have been teaching math for 34 years and feel I can follow the flow of a problem, but I teach my students to include everything to make sure their work is understood.Even the examples that are worked out sometimes have little to do with the problems that you are asked to solve.All in all, I feel this book is not well written for someone trying to learn these processes.

Terrible Book
This book deserves NO stars. I used it for a class and it must be the worst textbook I've ever seen. Its descriptions are cryptic and designed for PH.D's at best. If you expect to learn on your own from this book, give up. I tried because my prof didn't know english. i failed. For the record I'm a 4.0 student at MIT, so when I say this book is a terrible book, I'm not just randomly spouting. ... Read more

Product Description
This book emphasizes the theory of mathematical statistics while using applications and precise language to help illustrate points and motivate students. This new edition features exercises throughout each chapter; presents a dual approach to hypothesis testing - basing decisions on statistics and critical regions or P-values; expands coverage of estimation; treats analysis of t x c tables with ordered categories; and discusses robustness for estimation and testing hypotheses. ... Read more

Product Description
A balanced presentation of both theoretical and applied material with numerous problem sets to illustrate important concepts. Demonstrates the use of computers and calculators to facilitate problem solving, as well as numerous applications to illustrate basic theory. ... Read more

Customer Reviews (3)

good text on mathematical statistics
Paul Hoel taught statistics at UCLA for many years.This book was one of the best introductions to mathematical statistics for a first year graduate course.It was used as a text for that purpose at UCLA and many other statistics departments across the country.Several editions of the book were published to keep it up to date.Currently it is a little dated and there are many advances particularly in the area of resampling methods and other computer-intensive statistical procedures that are not covered.

I think it is somewhat comparable to the combination of Erich Lehmann's books on hypothesis testing and the theory of estimation.

Statistical theory and application
I used the fourth edition in a college course and found it to be well written and very understandable (the fourth edition was pre-calculator and had math tables in the back).The book assumed only an elementary calculus background and so was not rigorous in proving every theorem introduced, but was pretty good in showing the derivation of commonly used results and formulas.

I particularly liked the problem sets which were a mix of theoretical and applied exercises (with answers to the odd numbers), and NOT a long list of statements to be proven.

The emphasis was on theory, but statistical theory developed from attempts to solve real life problems and this book recognized that and considered applications of that theory throughout.

Encyclopeadia Britannica
I knew this book's name from Bibiography for an Encyclopeadia Britannica (1993 edition) article Statistics. I have not read the book yet. I gave it a neutral rating (3 stars) since I assume the book at least is not a poor one. (Very likely it deserv a 4 or 5 star rating after I read it). ... Read more

Product Description
Noted for its integration of real-world data and case studies, this guide offers sound coverage of the theoretical aspects of mathematical statistics. It demonstrates how and when to use statistical methods, while reinforcing the calculus that readers have already mastered.Presents standard statistical techniques in a mathematical context, allowing the reader to see the underlying hypotheses for the applications. Uses case studies and practical worked-out examples to motivate statistical reasoning and demonstrate the application of statistical methods to a wide variety of real-world situations. Discusses practical problems in the application of the ideas covered in each chapter, as well as common misunderstandings or faulty approaches. Revised Minitab sections now conform to the Version 14, the latest release.For anyone interested in learning more about mathematical statistics. ... Read more

Customer Reviews (15)

Well done
I am surprised by the number of negative reviews for what I consider to be a nicely written, well thought out, and logically presented introductory course on mathematical statistics. Yes, a working knowledge of elementary calculus is a prerequisite. But the mathematics invoked in the exposition of concepts and theorems are kept as simple as possible while maintaining that modest level of rigor appropriate for a introductory exposition. If you do not have the minimal mathematical prerequisites (such as freshman calculus), blame your instructor or your schoolfor selecting an inappropriate text. But don't blame the authors! I thought the examples and problems were appropriate in their level of difficulty (mostly not so hard) and the relation to the material just covered. There are plenty of poorly written, impossibly dry, inpenetrable texts on statistics out there - this is not one of them. In addition, the book is attractively packaged, the paper quality is excellent, the visuals are informative and clearly presented - that also should not be taken for granted. Lastly the authors have a wicked entertaining sense of humor that spice the presentation throughout.I consider this book to be a welcome addition to the set of modern textbooks available to the curious serious student of probability and statistics.

dry and difficult
In case you're unclear on the matter, "mathematical statistics" is code talk for "statistics with calculus."So don't think this is book is a high-school or even undergraduate-level "introduction" for statistics.For that I would recommend the friendlier but still meaty Stats: Modeling the World (2nd Edition) (DeVeaux/Velleman/Bock).

At my university, this book is usually used in the first math class required of those in graduate school majoriing in the statistical social sciences.

So make sure you're ready.The authors assume you are quite solid at the calculus.

Confused and confusing
I used this as the text in a sequence on probability and statistics I taught recently, and I soon came to regret this choice. The authors are obviously quite confused about basic concepts. Here are some examples: the "definition" of the median ignores obvious problems with existence and uniqueness; the "proof" of the central limit theorem is thoroughly incomplete; the "theorems" on the tests in Sect. 9.2, 9.3 summarize previous discussions, but the "proofs" of these theorems (we are even referred to an appendix - no small surprise when the statements seem obvious) establish something entirely different; finally, to conclude this (very incomplete) selection, there is the delightful claim that the golden ratio is a transcendental number (which just proves that the authors don't have the slightest idea what a transcendental number really is, but then it might have been wise to avoid the use of the term).

In addition to these blatant problems, the authors' treatment frequently misses the point and/or is confusing.

Infuriating
The text presents all relevant information, but does so in such a confusing and poorly explained fashion as to prompt the reader to wonder if the authors have ever met anyone who hasn't known all subtleties of probability since the womb.There is no avenue for the student who does not understand, no pedagogy whatsoever.Everything is presented at lightning pace with blisteringly difficult proofs and, often, no meaningful explanation of the physical meaning of the concepts explained.A very solid background in calculus is an absolute necessity, to the point where many problems in the text are more challenging in evaluating integrals than they are in actually applying concepts.This is a serious problem that recurs over and over.

Examples worked out in the chapter sections also almost never bear any resemblance to the problems students are expected to complete.Although the examples vary in terms of difficulty, a student stuck on an exercise almost definitely will not find any help in the teaching material of the section in completing it simply because the examples never entirely cover the concepts demanded in the exercises.

s

Excellent intro to the mathematics of traditional statistics
The first half of the book begins with basic discrete and continuous probability theory.It continues with thorough overviews of the basic distributions (normal, Poisson, binomial, multinomial, chi-squared and student-T).The focus is on basic probability and variance analysis, though it briefly covers higher-order moments.

The second half of this book is devoted to hypothesis testing and regression.There is an excellent explanation of the mathematical presuppositions of the various classical experimental methodologies ranging from chi-square to t-tests togeneralized likelihood ratio testing.It contains a very nicely organized chapter on general regression analysis, concentrating on the common least squares case under the usual transforms (e.g. exponential, logistic, etc.).

Like many books in mathematics, this introduction starts from first principles in the topic it's introducing, but assumes some "mathematical sophistication".In this case, it assumes you're comfortable with basic definition-example-theorem style and that you understand the basics of multivariate differential equations.I was a math and computer science undergrad who did much better in abstract algebra and set theory than analysis and diff eqs, but I found this book extremely readable.I couldn't have derived the proofs, but I could follow them because they were written as clearly as anything I've ever read in mathematics.I found the explanation of the central limit theorem and the numerous normal approximation theorems for sampling to be exceptionally clear.

The examples were both illuminating and entertaining.One of the beauties of statistics is that the examples are almost always interesting real-world problems, in this case ranging from biological (e.g. significance testing for cancer clusters) to man-made (e.g. Poisson models of football scoring) to physical (e.g. loaded dice).The examples tied directly to the techniques being explored.The exercises were more exercise-like in this book than in some math books where they're a dumping ground for material that wouldn't fit into the body of the text.This book has clearly been tuned over many years of classroom use with real students.

I read this book because I found I couldn't understand the applied statistics I was reading in machine learning and Bayesian data analysis research papers in my field (computational linguistics).In paticular, I wanted the background to be able to tackle books such as Hastie et al.'s "Elements of Statistical Learning" or Gelman et al.'s "Bayesian Data Analysis", both of which pretty much assume a good grounding in the topics covered in this book by Larsen and make excellent follow-on reading. ... Read more

Product Description

This innovative new introduction to Mathematical Statistics covers the important concept of estimation at a point much earlier (Chapter 2) than others on this subject. Applies mathematical statistics to topics such as insurance, Pap smear tests, estimating the number of whales in an ocean, fitting models, filling  12 ounce containers, environmental issues,  and results in certain sporting events. Includes summaries of the most important aspects of discrete distributions, continuous distributions, confidence intervals, and tests of hypotheses. Provides computer applications for data analysis and also for theoretical solutions such as simulation and bootstrapping.A comprehensive reference for individuals who need to brush up on their knowledge of statistics.

Customer Reviews (1)

Worst Math Book
I took Mathematical Statistics I and am currently in Mathematical Statistics II. This book has been like nails on a chalk board to me. The examples are unclear and are mostly made up of theories. In many sections, the author writes questions before the exercises and does not answer them! I am a math major and I understand advanced math classes are proof and theory based; however, I've worked with a Linear Algebra book that gave clear and easy to understand material. I recommend finding another Statistics book and stay away from this book! ... Read more

Product Description

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Fully compatible with your classroom text, Schaum's highlights all the important facts you need to know. Use Schaum's to shorten your study time-and get your best test scores!

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Customer Reviews (7)

very condensed
This book and the way it's advertised make it seem like an idiot's guide to Stats. However, it's not. It's actually pretty dense for that. It is a great supplement to a Stats class. It cuts through a lot of the nonsense and verbiage of many stats texts. I'd suggest using this to supplement the class (after lectures etc). It's also great to refresh yourself on basic stats and probability concepts once you've taken a course. I just wish it had more diagrams and pictures of the various distributions.

Good book!
I really love this book. The packaging is super nice.. There was no single damage to my book.. I just LOVE it

Riddled with Typos
I thought the material covered in this book was excellent and the examples are very good as well, but there was just one problem....riddled with typos.I noticed the first one on a Supplementary Problem in the the first chapter: the given answer was way off. Then in the 2nd chapter I noticed on another practice problem that there was an addition sign instead of an equal sign.Issues like this popped up for me through the FIRST 5 CHAPTERS!!!! If you are just learning some of this material it can be extremely frustrating because one symbol or number that is off may cause you to rack your brain for hours trying to figure out if it's the book or you that is wrong. Because most students blindly trust books this can cause a real hiccup in your studies.When I finally got fed up with the book I had to call McGraw Hill to see if they could exchange it for one without all the errors. Because I didn't purchase it directly from them (as most individual students purchase books from a store) they said there is nothing they could do for me except inform the editors.When I asked them if they accept any product liability on their part their response was: "If you buy food from one grocery store you can't return it at another". I urge you that if you are learning this material for the first time STAY AWAY FROM THIS BOOK.I gave this book 2 Stars because the content and explanations were pretty good, but the typos eventually became too much to overlook.

Probability and Statistics
Probability and Statistics is my life. I needed this book to just refresh my basic stats and this is it.

great deal
awesome price, came within a reasonable amount of time, came in good condition, no complaints whatsoever ... Read more

Product Description

John Fox’s A Mathematical Primer for Social Statistics covers many often ignored yet important topics in mathematics and mathematical statistics. This text provides readers with the foundation on which an understanding of applied statistics rests.

Key Features

· Covers matrices, linear algebra, and vector geometry

· Discusses basic differential and integral calculus

· Focuses on probability and statistical estimation

· Develops by way of illustration the seminal statistical method of linear least-squares regression

Intended Audience

This book is ideal for advanced undergraduates, graduate students, and researchers in the social sciences who need to understand and use relatively advanced statistical methods but whose mathematical preparation for this work is insufficient.

Customer Reviews (1)

An Excellent Primer on Mathematical Concepts for Statistics
This gem of a book provides a concise and quite readable overview of important mathematical concepts that are important for understanding both basic and advanced statistical methods, not only for sociologists, but any practitioner of applied statistics. John Fox has successfully pulled together and integrated into a 166 page primer mathematical concepts that often appear scattered in more advanced mathematics courses, including advanced calculus courses that many users of applied statistical methods might not have taken. The book starts with an introduction and overview of matrices, linear algebra, and vector geometry. The material in this chapter is absolutely essential to anyone who wishes to use multivariate methods such as principle components analysis and should be mastered even if the reader chooses not to finish the book. The following chapter provides an astonishingly practical review of differential and intgeral calculus concepts important to statistics; after a brief review of planes, functions, and limits of functions, Dr. Fox quickly reviews differentiation of functions,optimization problems involving derivatives, multivariate and matrix differential calculus, Taylor's theorem, and finally an overview of integral calculus whose concepts are important in understanding probability distributions. Chapter 3 provides an excellent introduction to mathematical statistics to include properties of various distributions and estimators, maximum-likelihood estimation, and an introduction to Bayesian inference. Chapter 4 entitled "Putting the Math to Work: Linear Least Squares Regression" closes out this primer and shows how the method of least squares and the Gauss-Markov Theorem is used to estimate regression parameters and associated statistics. All in all, this is an excellent and highly readable overview of mathematics concepts that can function to fill the "math gap" that many users of statistical methods often have due to inadequate math preparation. At ~$16, the book is a smashing bargain. Very highly recommended! ... Read more

Product Description
This book and software package presents a unified approach for doing mathematical statistics with Mathematica. The mathStatica software empowers the student with the ability to solve difficult problems. The professional statistician will be able to tackle tricky multivariate distributions, generating functions, inversion theorems, symbolic maximum likelihood estimation, unbiased estimation, and the checking and correcting of textbook formulae. This is the ideal companion for researchers and students in statistics, econometrics, engineering, physics, psychometrics, economics, finance, biometrics, and the social sciences. The mathStatica CD-ROM includes: mathStatica: The Applications Pack for mathematical statistics, custom Mathematica palettes, live interactive book that is identical to the printed text, online help, trail version of Mathematica 4.0. Colin Rose is Director of the Theoretical Research Institute (Sydney). He has published in leading journals on computer algebra systems and their applications to statistics, economics, and finance. Murry Smith is a senior lecturer in the Department of Econometrics and Business Statistics at the University of Sydney. In 1998-99, he was awarded an Alexander von Humboldt Research Fellowship to visit the University of Munich. He publishes in the fields of statistics, econometric theory, and computer algebra systems.

WINNER of The MDTech Prize for Best Software Contribution at COMPSTAT 2002! ... Read more

Customer Reviews (16)

Expensive book, even more expensive software
Just wanted to echo the other reviews and point out that you'll be out $200+ (for academics/students) to get a working version of the software. The book is not very useful without the software, unless you have not been using Mathematica for many years and are still on version 4. I'm highly disappointed, as I am now out the cost of the book, and can't do anything unless I spend $130 more.

Total con. You need to spend another $585, and hope they update for version 6
This is really a software manual rather than a book. Unfortunately, in order to use the software you will have to use a really old edition of Mathematica, or use version 5.2 and spend another $585 for the upgrade to make the software work. It is not $89 as some state - that is only for student/academic price.

Just to make matters worst, the $585 upgrade only works with 5.2, not 6, but they claim they will give you a free upgrade when it appears.

I feel that they should make a version available for no extra charge that works with current versions of Mathematica. Mathematica 5 (which the software does not work with), was released in 2003. There is no excuse for keeping the book in print, updating the software, but not making the updates available free of charge. I could accept updating only sufficient to work (no enhancements), but this is just a con.

I will be contacting Springer (the publishers) to complain. Will others do likewise?

Great stuff (with caveats)...Even more caveats
UPDATE JULY 2009:

As of 3Q09, they have still not released the software compatible with Mathematica 7.0 leave alone 6.0. A delay of a little less than 2 years - completely unacceptable for a software. Anyway, I think Wolfram is effectively going to put them out of business. Check out these new capabilities in Mathematica itself, rendering a lot of mathstatica's features obsolete.
[...]
Also, it look like their "bait and switch" tactics are still causing a lot of heartburn. I am revoking a couple of stars.....(as soon as I figure out how:)

ORIGINAL REVIEW:

This review is more about the software that accompanies the book rather than the chapters in the book itself. (which of course, is the whole point of the book).

I bought this product about 6 months ago, while I was in the middle of writing a couple of papers and found this to be a great tool. This is one of those rare products that makes useful but complicated things simple and easy. Even those of us who are gifted enough not to be turned off by symbolic prose will agree that there is a certain resistance to explore and learn something that's got mathematical symbols all over it - this piece of software will help overcome exactly that, not to mention how good Mathematica is by itself.

Having said that, if you are not comfortable say, at the level of "Statistical Inference" by Casella and Berger (one of the best books on the topic ever written), then this will do much less for you than you read in its reviews. Also I see from quite a few previous reviews that there is resentment at the authors not being totally upfront about the fact that it requires at least another $[...] (student version) to harness the power of this software totally. The professional version will set you back by about $[...].

Pros:

Great software. It does amazing things that used to take me hours by hand. Seemingly ugly or unsolvable problems are easily attacked.

Great customer service - I have emailed them a few times both about installation AND STATISTICAL questions and they are great with both. Seem like a pretty well run shop. Despite other reviews, the price is worth it.

Of course, if price is too much of a concern and you have all the time in the world, you can program these in Mathematica yourself - but these pre-programmed functions are much better. (I have tried).

Cons:

Not for a novice or statistical enthusiast. Please read the title - It does say "Mathematical Statistics" for Mathematica. So make sure you are at least at the level of Hogg/Craig or Casella/Berger etc.

As of 3/08, this is not compatible with Mma 6.0, but the website says they will be releasing the next version in 1Q 08, may be by the end of the month.

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

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

Customer Reviews (1)

Excellent Introduction to Mathematical Statistics
Excellent Introduction to Mathematical Statistics

Introduction to Mathematical Statistics

by Robert Hogg and Allen Craig (First Edition through Fifth Edition)
by Robert Hogg, Joseph McKean and Allen Craig (Sixth Edition)

Publication History:

First Edition
* (Year 1959)
* (245 pages)

Second Edition
* (Year 1965)
* (383 pages)

Third Edition
* (Year 1970)
* (415 pages)

Fourth Edition
* (Year 1978)
* (448 pages)
* (ISBN-10: 0029789907)
* (ISBN-13: 978-0029789902)
* (ISBN-10: 0023557109)
* (ISBN-13: 978-0023557101)

Fifth Edition
* (Year 1994)
* (576 pages)
* (ISBN-10: 0023557222)
* (ISBN-13: 978-0023557224)

Sixth Edition
* (Year 2004)
* (692 pages)
* (ISBN-10: 0130085073)
* (ISBN-13: 978-0130085078)


I read the third edition when it was first published.I was in school; I used it in an undergraduate class.Since then "Hogg and Craig" and now "Hogg; McKean and Craig" has been a regular reference work for me.

The only editions I've only read completely are the third edition and the sixth edition; I have used the fifth edition as a reference source since it was published first published.The coverage of mathematical statistics is concise and very thorough in all the editions.

The chapter on "Sufficient Statistics" is the clearest presentation I have ever seen.The chapter "Theory of Statistical Tests" is a very advanced treatment but very easy to use for any practitioner.

Another of my favorites is the last chapter on "Non-Parametric Statistics."

The following are good backup references and books that expand on ideas covered in "Introduction to Mathematical Statistics."


Other references on mathematical Statistics:
* (Mathematical Methods of Statistics. (PMS-9))
* (Introduction to Probability Theory and Statistical Inference (Wiley Series in Probability and Mathematical Statistics. Probability and Mathematical Statistics))
* (Random Variables and Probability Distributions (Cambridge Tracts in Mathematics))


Probability Theory
* (An Introduction to Probability Theory and its Applications: Volume I (Third Edition))
* (An Introduction to Probability Theory and Its Applications, Volume 2)


The Linear Model
* (Linear Models for Multivariate, Time Series, and Spatial Data (Springer Texts in Statistics))
* (Regression Analysis: Theory, Methods, and Applications (Springer Texts in Statistics))


Non-Parametric Models
* (All of Nonparametric Statistics (Springer Texts in Statistics))
* (Nonparametric Statistical Methods, 2nd Edition)
* (Analyzing Categorical Data (Springer Texts in Statistics)(Wiley Series in Probability and Statistics))


I've enjoyed this book since I first read it in 1971.The new edition is every bit as practical and enjoyable as the older editions.I recommend it to others with no reservations.


... Read more

Product Description
The aim of this graduate textbook is to provide a comprehensive advanced course in the theory of statistics covering those topics in estimation, testing, and large sample theory which a graduate student might typically need to learn as preparation for work on a Ph.D. An important strength of this book is that it provides a mathematically rigorous and even-handed account of both Classical and Bayesian inference in order to give readers a broad perspective. For example, the "uniformly most powerful" approach to testing is contrasted with available decision-theoretic approaches. ... Read more

Customer Reviews (4)

Another five star review for Schervish's ToS
I've decided that whenever I find a truly great textbook I need to go on the record and say so (giving me license to complain incessantly about all the crappy ones).Everything the other reviews have said is spot on.The organization of this book is a particular strength.The interesting sections on sufficiency and exchangeability, which go so far as to cover partial exchangeability and the theory of extremal families, aren't covered in many other textbooks. When I teach my first graduate level statistics course, this is the book I will use.

Best book on Theory of Statistics
This is undoubtedly the best book written on the theory of statistics.Author's explanations are mathematically rigorous. Ideal for the 2nd year graduate student who wants a full understanding of statistical inference.

packed with theory
This a very good book that covers all the traditional topics in the theory of statistics.A book at the graduate level like Cox and Hinkley or the combination of Lehmann's two books.This is the book you get if you want a comprehensive treatment of the subject.

If you are interested in a more concise text,see Essentials of Statistical Inference by Young and Smith.Not only does it concentrate on key results but it also provides the newest material including resampling and MCMC snd presents results from the perspective of the three major schools of statistical inference.For more detail see my review of that text.

comprehensive, modern, rigorous treatment of stat theory
This is the best book I've found that takes a modern approach to statistical theory at the advanced undergrad or graduate level.Schervish covers the necessary probability background, classical and Bayesian decision theory, and hypothesis testing comprehensively, while maintaining a level of rigor suitable for math majors (the appendix nicely summarizes requisite results from measure theory and mathematical probability).It covers most if not all of the classical results found in Lehmann's TSH and TPE, but from a more modern perspective.This permits a more coherent, well organized presentation.The only (minor) drawback I found were some typos here and there -- to be expected from a first edition of a 600 pager.It was a joy to study from this book. ... Read more

Product Description
Many mathematical statistics texts are heavily oriented toward a rigorous mathematical development of probability and statistics, without emphasizing contemporary statistical practice. MODERN MATHEMATICAL STATISTICS WITH APPLICATIONS strikes a balance between mathematical foundations and statistical practice. Accomplished authors Jay Devore and Ken Berk first engage students with real-life problems and scenarios and then provide them with both foundational context and theory. This book follows the spirit of the Committee on the Undergraduate Program in Mathematics (CUPM) recommendation that every math student should study statistics and probability with an emphasis on data analysis. ... Read more

Customer Reviews (2)

...
Very well written book compare to most statistics books with no structure this one have everythgin explained

Unpolished
Bottom line:A good complementary book and a buy if you are a Science (sampling concept is explained very sloppy; just here and there), Engineering, or CS student.

First of all I only read the beginning chapters of this book and I'm no Mathematician--but an avid Mathematics lover.I bought this book based on authors credentials and it turns out that the content does reflect upon it. If you want to have an understanding when you do statistics computation, then this book is highly recommended.Ideas of distribution of variables is copiously conveyed (ie. sampling location, exptected value of normal distribution).There's two sides of Mathematics, computation and formalization.Since probability is based on set operation--and book titled as Mathematical statistics, a coverage on set basics is necessary; or at least an appendix.I find also some definitions very loosely put (it is "menglish"), maybe the authors try too hard to convey to readers the "you can do it".

Summary:
(+)
.Statistics computation concept
.Examples that can be easily seen daily
.A good list of probability distribution models and processes

(-)
.Experimental sampling and set coverage
.Can be too wordy and confusing (overdo explaination) ... Read more

Product Description
This classic, time-honored introduction to the theory and practice of statistics modeling and inference reflects the changing focus of contemporary Statistics. Coverage begins with the more general nonparametric point of view and then looks at parametric models as submodels of the nonparametric ones which can be described smoothly by Euclidean parameters. Although some computational issues are discussed, this is very much a book on theory. It relates theory to conceptual and technical issues encountered in practice, viewing theory as suggestive for practice, not prescriptive. It shows readers how assumptions which lead to neat theory may be unrealistic in practice.Statistical Models, Goals, and Performance Criteria. Methods of Estimation. Measures of Performance, Notions of Optimality, and Construction of Optimal Procedures in Simple Situations. Testing Statistical Hypotheses: Basic Theory. Asymptotic Approximations. Multiparameter Estimation, Testing and Confidence Regions. A Review of Basic Probability Theory. More Advanced Topics in Analysis and Probability. Matrix Algebra.For anyone interested in mathematical statistics working in statistics, bio-statistics, economics, computer science, and mathematics. ... Read more

Customer Reviews (15)

Terrible book
This is the first time that I encountered a textbook that has so many typo errors (terrible enough, most of them are in the equations!) The errors literally reach an extent that will impact your understanding of the contexts smoothly. Given the authors are 2 mathematicians and the publisher is one of the best recognized textbook publishers in the world.....I seriously doubt they ever read the proof before printing. I regret I spent the money to buy this piece of junk.

First Edition much better than Second
The First Edition is a Classic; often the best and only book you need to learn practical statistics if you come from another field.

The Second Edition is reasonable, and the major changes the authors made to the First Edition are understandable from one point of view, but they did not succeed in equalling the quality of the First Edition.

The Second Edition is still a good introductory text on Statistics, but I recommend the First Edition if you can find it.

one of the best
This is one of a number of good first year graduate texts on statistical theory. It was used at Berkeley for their students in the late 1970s and early 1980s. These authors put together many interesting and challenging exercises at the end of the chapters. However they did not provide solutions to any of the problems. When Marc Sobel was a graduate student, his father Milton, a statistics professor convinced Marc to work out every problem in the book! Marc did this and eventually he and Milton put together a solution manual which was published. In the process a number of mistakes were caught and corrected.
If you get the book try to get the solution manual as well. It will greatly deepen your understanding of the material and help you through the difficult problems.
My review pertains to the original book by Bickel and Doksum that was published in 1977 by Holden-Day. I was under the misimpression that Prentice-Hall was publishing a reprint of the old book due to its popularity and the non-existence of the original publisher. I was apparently mistaken as the title indicates Volume 1 of the Second Edition. This was pointed out to me by a reader.

In general if you have doubts check with the reviewer about the edition for books with multiple editions. Often reviewers write reviews for a particular edition and when the new edition comes out it accidentally gets moved. This can happen when amazon removes the page for the old edition because it no longer carries it. Reviews of old editions can still be helpful since the heart of the book usually remains the same and the quality of writing of the authors does not often change much. Of course a review of the new edition would be better if it has information on changes and additions and any particularly attractive new features of the book.

mathematical statistics: basic ideas and selected topics
Good book, well written and complete (illustrated by examples).
not adapted for beginners. A good level on mathematics is needed
for a complete understanding

Please pull this book from circulation.
Nearly everyone is correct about this new edition of a book previously held in high regard.This book should be pulled from publication until it has been corrected and issued with Vol 2.This book is in bad enough condition to psychologically damage an entire generation of statisticians.The original edition is not currently in print, but other (better) options exist.Consider "Introduction to the Theory of Statistics" by Mood & Graybill, "A First Course in Mathematical Statistics" by Roussas, "Linear Statistical Inference" by Rao and "Optimal Statistical Decisions" by DeGroot.They are older, but are correct and still fundamentally relevant. ... Read more

Product Description

This book is based on the view that cognitive skills are best acquired by solving challenging, non-standard probability problems.

Many puzzles and problems presented here are either new within a problem solving context (although as topics in fundamental research they are long known) or are variations of classical problems which follow directly from elementary concepts. A small number of particularly instructive problems is taken from previous sources which in this case are generally given. This book will be a handy resource for professors looking for problems to assign, for undergraduate math students, and for a more general audience of amateur scientists.

Customer Reviews (1)

May way for the modern puzzle book
What an excellent, excellent problem-puzzle book! This book lays the groundwork for puzzlers of the 21st century.

At a buck a puzzle, every aspiring/amateur probabilist should buy this book... and while you're at it, buy one for your dramatist brother. ... Read more

Product Description
The Second Edition of INTRODUCTION TO PROBABILITY AND MATHEMATICAL STATISTICS focuses on developing the skills to build probability (stochastic) models.Lee J. Bain and Max Engelhardt focus on the mathematical development of the subject, with examples and exercises oriented toward applications. ... Read more

Customer Reviews (12)

The Horror The Horror
God help you if you are inflicted with this book for a class on mathematical statistics. You'll really need to depend on your professor's lectures to learn anything. As other reviewers have said, the examples are too easy and the problems are too hard. Be sharp on your algebra and calculus, as you're going to need it - many solutions require difficult integrals and rarely used algebra theorems. In addition, the examples in the text are terse and not explained very well. Often an example will have a statement like, "Obviously, since A=B, then" - well, it isn't obvious that A=B and you have to spend 5 minutes figuring that out (often referring to prior chapters). Or they'll present a proof and not explain the steps - again, more time figuring out what the heck they're doing. As for the problems - very hard - and often you have to spend a lot of time just trying to figure out what is really being asked. Probably a great book if you already know mathematical statistics, but if you're trying to learn it for the first time . . . run away! run away! The worst mathematics book I've ever used - even worse that Advanced Engineering Mathematics by Kreyzig.

Exam P
I bought this book for my BYU STAT470 class.The class is designed to prepare you for SOA Exam P, but I found the book hard to navigate and really doesn't offer much in the form of exam practice.I feel that the ACTEX manuals are a much better resource for learning Exam P material.

Good book
The book is a good intermediate book.I was able to build off this and reference this book in my other mathematical statistics courses.

The quality of the book was as described and it shipped quickly.

Is it really that bad?
I'd like to say that this book, while hard, is a good book. It goes through semi-simple examples and then leaves the student to work through a bit more difficult problems that gives the ability for the student to expand his or her mind in the material, which is needed in a mathematical field. However, I definitely would not suggest it as a book to learn from on your own just for this reason because you really need a teacher to go to and ask questions. I liked the book because it goes way more in depth on the theory than others I have looked through, so beware if your math skills are not up to par. Just to let you know, we used it for a half undergrad/half graduate course at my school and this was my first class in statistics. It wasn't horrible.

Graduate Probability and Statistics
This book is great for graduate studies in Probability and Statistics. However, you will need some mathematical maturity because some of the exercises contain mathematical proofs involving Calculus. I must admit that this book could be challenging at times, but that doesn't mean one should degrade the book. I like this book and I highly recommend it. You will obtain a great foundation in Probability and Statistics after using this book. I actually used this book as a text during my undergraduate studies, but I think only advanced undergraduates can handle it. ... Read more

Product Description
A classic, calculus-based introduction to the theory — and application — of statistics.Provides comprehensive depth and breadth of coverage and reflects the state-of-the-art in statistical thinking, the teaching of statistics, and current practices — including the use of the computer. ... Read more

Customer Reviews (7)

Decent but severely overpriced
I used this book for a 300 level undergraduate probability course. I'm glad it's over now!

Pros:
1) The book is set up in a straightforward way, running from counting techniques to probability and then statistics.
2) The examples were pretty helpful.

Cons:
1)PRICE!!!!!!!! Every college student knows that textbooks are overpriced these days. The companies seem to justify this by adding links to related web content, putting color photos/graphics on every page, etc. This book has none of this! It's all black and white! All the graphs look like they were done on an Apple II! Hey, I like pictures as much as the next guy, but but a 6 year old edition of 600 black text pages is not worth $100!!!!!!
2)No solution manual--for some of the more complicated problems, you need the solution manual, not just a numerical answer at the back of the book.

Verdict:
If you have to buy this, but it used! Stand up to textbook price-gouging!

An average reader
With a very limited background in theoretical probability & statistics (as was the case for me), this book is no doubt a challenge and requires serious patience at times. However, the effort really paid off in the end, leaving me with a both intuitive and in-depth understanding of important statistical concepts. The only real frustration was that there are only answers to half of the exercises, and even these are not worked out. Having a solution manual with worked solutions to all problems would have EASILY made this a 5-star book.

Very precise with plenty of proofs
This book differentiates itself from other mathematical statistics books by the accuracy of its content (almost no errors). Multivariable Calculus is definitely a prerequisite to this book though, and many of the exercises and examples deal with proofs. I would have given the book 5 stars but it lost points for two reasons:

1.) The latter chapters (after chapter 3, except the applications chapters) include almost no applied examples.
2.) The authors have a bad habit of introducing new problems in the exercises.

I can't think of any proofs that were neglected, and all of the proofs were elegant and complete, but very few applied examples were given. Despite these shortcomings I liked the book and feel it is a good calculus based introductory book to mathematical statistics. If you are looking for a deeper understanding of statistics and the mathematical theory behind statistics then this is a great book for you!

Freund continues to surf the statistical waves!
Freund's Mathematical Statistics remains an utterly fantastic book for the seriously motivated learner of statistics!I'd recommend it in a heartbeat to anyone who wants a good intermediate-level introduction to mathematical statistics.Although it seemingly lacks a CD ROM and solution guide (if there are any, please inform Amazon.com), I find it most challenging, and, quite frankly, exciting.A great source of information!

Unbelievably expensive for the quality
This is the kind of book that gives college textbooks a bad name. .... Let's see, that's, uh, 17 cents a page. To boot, the writing is lousy, bold-face definitions spoty and buried, and included disk basically worthless (you'd think they'd spend some of their profit on a CD that all computers can use, but they didn't...). As for the 5-star reader, how much you want to bet it's the author? ... Read more