5 comments about Geometry the Easy Way.

1. I LOVE this book as the directions are clear! I use this book as a back up to my daughter's classroom instructions as this book is used as reinforcement to her class work! I have not had Geometry in YEARS and I wished I had this book during my own schooling! Buy this book because it is helpful!



2. I am using this book to bolster my geometry skills for the GMAT, and this book has been excellent. The only reason why I gave it a 4 stars instead of 5 stars is that I wish it worked out the more difficult problems for you step-by step.



3. 30 years after taking Geometry in High School, I started back to college recently to get my degree. Problem: I had forgotten almost everything I had learned 30 years ago, and not only that, but 30 years ago I hadn't really paid much attention and didn't learn the material well anyway. I discovered this book "Geometry the easy way" and it has been excellent. It is extremely well-written and the subject is made simple for almost anyone who desires to learn Geometry, including High School students. Obviously, Mr. Leff knows his subject well, and knows how to explain it the best way possible. I give it my highest recommendation, and I almost never write these reviews, so that's saying a lot from me.
   
   BTW, I tried "Algebra the Easy Way" and was extremely disappointed. I thought that book was terrible because it tried to tell a fictional story along with the material as a way of making it simpler, but it failed miserably with this tactic, at least with me.



4. This was a used book, so I had no idea what to expect. The book came as advertised, slightly worn, but no markings inside or out. Since I wanted the book for an aide in tutoring my grand daughter, it works out well. I was very satisfied with the book.



5. I have always sailed through math courses.
   I ordered this book to review for my upcoming job teaching HS Geometry
   at a new school. I couldn't believe this book! Not only is this NOT the
   easy way, but it leaves huge holes in guided practice. Where are the
   notes about how to properly work out these proofs? There aren't any. Unless you are good at totally figuring this stuff out by yourself, don't buy this book. There are many typos also, which is a big red flag!

5 comments about Zero: The Biography of a Dangerous Idea.

1. The book was something like 200 pages, but it read like it was a little more than that.
   
   The good points:
   
   1. An interesting demonstration of how things that are only of moment to intellectuals at one point in time become things of great significance later.
   
   2. An interesting demonstration of how ugly the fight for influence can be. (It is interesting to speculate that people now are no different to what they have been for the last 250,000 years, and that the motives of people who seek to "educate" others about environmentalism/ military-industrial complexes/ etc.) may not be as pure as what they seem.
   
   3. The perspective on the dynamics of the Catholic Church's suppression of contrary ideas was also very interesting. Many people (preferring to spout anti-religious screed) do not treat this fact as one set of intellectuals fighting to impose their vision to the detriment of some other set of intellectuals' vision-- which it in fact seems to be.
   
   4. It was interesting to note how slow the development of ideas was. Can a person really believe that it took nearly a thousand years to popularize the number "0" until he reads this book?
   
   Bad points:
   
   1. The treatment of differential calculus was diminished by the use of strange notation. It might have been easier to show how this would come up in the context of trying to solve a real problem rather than just presenting the idea the way that it was presented.
   
   2. The treatment of integral calculus is simply poor. He could have spent a few more pages on it without diminishing the book.
   
   3. The treatment of the Riemann plane was not good, either. I understood the calculus before reading the book, and so I could see what he was trying to get at. However, I didn't understand much of anything after that. So the weakness of the explanations became more evident when delving into new topics.
   
   4. The book could have used some additional appendices to flush out explanations that the author didn't want to put in the text of the book.
   
   5. The topic of the book seems to become a bit stretched at the end. It goes from explaining the intellectual history of zero to its uses in physics, and the transition is not smooth. One gets the feeling that the author was stretching to find a connection to finish the book.
   
   All in all, worth the purchase price of a secondhand book.



2. The thing I liked most about Zero was the humor & sarcasm thrown in by the author. It breaks up the seriousness & complexity of some of the topics he covers & relates to zero (i.e. Calculus, Quantum Physics). Seife gave plenty of examples & metaphors to help the average joe understand the overall concepts. He also goes deeper for those readers that are math buffs.
   
   While the entire concept of zero/infinity is constantly repeated throughout the book, I like the way the book was organized: chonologically. Zero begins with a history/religion lesson as it discusses zero's origin. Then, the book moves into philosophy/mathematics & zero's role. Last, the book covers topics on a much bigger scale such as astrology/physics/Big Bang theory, and how zero will affect the future.
   
   Zero kept me entertained, challenged me to think abstractly regarding religion/philosophy/our universe, and kept the tone very light. I have always struggled with math & hated the subject, but this book is more than a math lesson! Try it!



3. I'll admit, writing a book about nothing and making it exciting is probably a challenging thing to do. This is going to be a rather odd thing to bring up at the start of the review, but I have to ask did people read a different book than I did? Seriously, I read through just about every negative review and the points made against the book are barely in the book I read. If anything, they focus in on a minor detail, interpret it wrong, and then give the book a one star. I digress, let me get to the review and then I may go over some points to refute.
   
   This book focuses on the history of Zero for the most part. In there it touches upon historical moments in mathematics and later in physics as it gets to the modern scientific era. I personally found the research on the early history quite on point and very fun to read (there's a lengthy bibliography at the end if you feel the need to see his words backed up). The sensational writing didn't bother me at all, because I realize the relationship between the title and the style. Seife is trying to make nothing exciting! If you didn't get that point or got annoyed with that style then you missed out on a really fun read. The author tried to include fairly random historical anecdotes about the people discussed to lighten the mood in the book. I thought these were fun additions and interesting to read as well.
   
   Overall the book is written in decently easy to understand language. I have a fairly decent mathematical background and I didn't feel I really needed to know everything to read the first half of the book. However, when Seife starts delving into concepts like Calculus and Set Theory I think knowing how to do calculus was definitely a help in understanding this section. If you're more of a lay reader and more interested in the history than the math then this book really might be a bad choice. The first part is absolutely fascinating, but it does get confusing towards the end, especially when he starts delving into Quantum Theory and Particle Physics.
   
   One aspect on the section of early history that I found particularly fascinating was the relation of zero to philosophy. The ancients were heavily influenced by beliefs and philosophy so it's not much of a stretch to think this influence stretched beyond just those subjects and into math and science. So when Pythagoras and Aristotle reject notions of the void philosophically it's reasonable to assume they would find such notions nonsense mathematically. For a long time, and still today, Math is merely a representation of the world we see and observe. They didn't observe voids or vacuum's during Aristotle's time so naturally they wouldn't exactly latch onto it as a real possibility. One thing that really fascinated me was the possible hindrance philosophy and belief (or religion) had in holding back mankind's ability to progress mathematically. The main reason that zero didn't make it into the western world probably had more to do with the stranglehold the Romans put on the people than with their unwilling to believe in the void or infinity, which is also why it was trade that finally used zero. However, there were intellectuals alive and breathing during the Dark Ages and a lot of their hindrance to accept concepts like zero was philosophical. The Church had adopted Aristotle's model of the universe and it was blatantly wrong. (This book does not say Aristotle is at fault for holding back people philosophically, it merely says his view/model, that the Earth is the center of the universe, is wrong. Which it is.) However, the rising power of the Catholic Church adopted his explanation and said it was a fact and back then their word was law. Once mathematics and science came across discrepancies in that proof then Church asserted its power and only tried to tighten its grip on those communities until people revolted against it. I'm not saying zero is the reason we got out of the Dark Ages, but it didn't hurt us any! It probably helped us a lot more in the long run. My point in bringing this up is that things like belief and philosophy can hinder progress in fields like the sciences. (These are not beliefs, as in making assumptions about testable criteria by the way.) It seems to make more sense, that if you must derive some divine notion, you would interpret the data, not try to fit the data into a preconceived belief. Thus belief would interpret the math and math would not interpret the belief. The ancients had this backwards for a long time, which I think that's a major factor and this book touches upon that.
   
   As I mentioned above the book can change gears into something very complicated. I think this is kind of the downfall of this book for some people because the confusing explanations at the end leave them on a low note. As the book progressed and got beyond my mathematical understanding I found the explanations a lot more confusing. When it finally got out of the confusing areas I think it picked up again during the sections on the expansion of the universe. I enjoyed the parts of Zero Point energy, but I'm not entirely sure it's written in a fashion that is easily understood. Seife makes comments in a very historical manner and I think that really confuses people at times. Such as one reviewer complained that the books information is outdated on Vacuums and concepts like limitless energy. However, this book does touch on that subject during its discussion of Zero Point energy, maybe it was merely presented in a way that confused readers? I'm not entirely sure; I didn't personally feel confused until he started talking about Set Theory, which I clearly need to brush up on.
   
   In the end I simply loved this book. I tore through it in a mere three days and I'm a pretty slow reader. I personally didn't mind the sensationalizing of zero to fairly emphatic levels. This is a book about nothing after all and you might as well make it sound really exciting! Maybe there should've been more exclamation points so we can see how impressive the author's thoughts really are! Anyway I had fun with this book, but I wouldn't recommend it to people that haven't made it beyond calculus or else the second half might get a little confusing. Previously understanding Einstein's work would be a bonus to getting through this book as well. Other than that the first half is absolutely fascinating and I feel I walked away with more knowledge than I went in even if the book repeated a lot of things I already knew.
   
   Overall Rating: 4.5 out of 5



4. This book can be read on two levels: 1) History, insight, personality and amusement or 2) technical terms and formula. Most of us will want to forget the second part and concentrate on the first part. Do that and this is a really good book.
   
   Read for the first reason, this is a fascinating, enjoyable, intriguing, informative, even useful read. Read how some of the great names in mathmatics, history, logic, even religion, lived and died, how the church killed people because they believed in zero, the void, the nothingness and the infinity.
   
   Read for the second reason--logic, high math and calculus--it is above most, if not all, casual readers.
   
   The key is knowing how to read the book, knowing when to read, laugh, learn and be amused and when to skip over the technical "stuff."
   
   This book is highly recommended--you will find it fascinating, amusing, sometimes amazing and educational--if you read it right!!



5. In Zero: the Biography of a Dangerous Idea, Seife first gives the history of the zero, in mathematics and social history, as well as it's non-history (why it was rejected in some cultures). He explains the resistance of the Greeks to the idea of the zero, why the Catholic Church rejected the zero and also how it was used in much earlier societies. These first chapters are well worth reading, blending history, math and mathematical history in a fascinating tale.
   
   From there, the author begins to blend the idea of zero with other "dangerous" mathematical ideas (including "infinity"), and with his intermingling of ideas he looses the persuasiveness of his argument. It's hard to follow and/or believe that "zero" did this or that, when the zero he is talking about isn't actually "zero". Confused? So was I. He seemed to loose his focus and clarity from around chapter 6 to the end.
   
   There are some rather high mathematical principals and examples throughout the book, which were difficult for me (not the world's best mathematician) to follow, and Seife often assumes that if one is reading Zero, then one is a mathematician, not a layman. This occurred more often in the later chapters which were troublesome in other ways, so I might just not have been as willing to try to understand the math, as I was having a hard time understanding the author's arguments.
   
   On the whole, Zero: the Biography of a Dangerous Idea felt like a thesis that was expounded out to be a full-length book. It would have been much better, in my opinion, if Seife had stopped at around chapter 5, the first chapters being where his knowledge, insight and humor shone through.

5 comments about The Algorithm Design Manual.

1. Nice to have this book handy if you need to design efficient algorithms for your programs. This is more of a reference than to teach you what algorithms are out there, so you better know them before using this book. That said, this book is quite unique since it differs from a typical algorithm book on the market. Skiena has done a great job in presenting the material. I find this book really handy, definately recommanded.



2. There are many reasons I like this book more than other Algorithms books I own (e.g. Sedgewick). One is that Skiena's book comes with an HTML version, so it's easy to keep it with you at all times (e.g. on your laptop, at work, and at home). Another is the "war stories". I found that I wanted to read the war stories first, rather than the technical content. Another is that the book points you at existing implementations, which really is what you'll eventually need to look at if you're going to use or write any code.
   
   Overall, I found that when confronted to real world problems, the "Algorithm Design Manual" was a better resource than other Algorithm books. This is why I'm recommending it to software engineers out there. It seems to be written for people working with algorithms to solve problems, rather than as a support for an academic course.
   
   On the negative side: I find the resource catalog to be exhaustive but somewhat shallow. As I'm getting older and slower, some things are not as obvious as they used to be. For example, I was quite unable to derive how to use Voronoi diagrams to perform nearest neighbour search, although it is supposed to be "a simple matter".



3. I found this book extremely practical, especially for professionals that don't have everyday the occasion to be confronted with real algorithmic problems (I assume that most of the industry-related software programmers / designers / analysts are in this category), thus beeing in need to have a reference at hand "just in case" :-).
   
   Together with "Programming challenges" also from Skiena & co. constitutes a powerful known algorithms references, and supplied with some natural problem-solving talent, could be a succesfull preparation for something like ACM contests or topcoders.com



4. For those computer science students and programmers who are put off by the style of "Introduction to Algorithms" by Cormen et al., this book is a good alternative. Rather than just being a catalog of algorithms with code and little explanation, this book covers a much needed middle ground and contains a good deal about the analysis and design of algorithms in general along with discussions of common algorithms themselves in an accessible style. In fact, the author makes a point of mentioning in his preface that you will not find a single theorem in this book, and that the purpose of his book is to get working programmers up to speed quickly on both the generalities and specifics of algorithm design.
   The first part of the book is on techniques, and covers the basics of modeling algorithms along with "Big Oh" notation, data structures and sorting, dynamic programming, graph algorithms, combinational search, and the concept of intractibility. What makes this section of the book particularly interesting are the author's "war stories" that talk about real world applications of the ideas discussed in each chapter.
   Part two of the book, "Resources", is an extensive catalog of algorithmic problems organized by type. For each problem mentioned, the book includes a problem description and discussion, possible implementations, and other algorithmic problems that are related to this one. In the implementation section for each algorithm, the author demonstrates the kinds of questions that the reader should ask when designing his or her own implementation. The C, C++, Fortran, and Pascal code for all algorithm implementations mentioned is on the accompanying CD rather than in the book itself, which helps make the book more compact.
   This book is a very good introduction to the methods of algorithm analysis and design, and an encyclopedic reference on many different types of algorithms. Highly recommended.



5. This book is splitted in two parts.
   The first part mostly contains general advices about algorithms, performances, and such.
   The second part is more like a huge catalogue of "classical" problems and algorithms related to those, with advices about how to work them. It does not contain algorithms or pseudo-code (or very little), but is more about how to address the problem (and also contains pointers to an implementation).

5 comments about Advanced Engineering Mathematics.

1. Only a few problems per chapter are explained/solved. Not worth the money. Really a paltry manual



2. GOOD:
   This book is useful if you need a fairly comprehensive reference book covering many mathematical topics in engineering.
   
   BAD:
   Most topics are treated too superficially to be useful as a primary learning text.
   
   STRANGE TARGET GROUP:
   If you could only have one math book after you've gone through all your undergraduate engineering courses, this might be a good pick. But that's a silly scenario. Instead, you'll probably be better off with four or five separate books that are focused on their subject.
   
   I don't regret purchasing this text, but I got it very cheap overseas... It's really not worth the current $132 price, in my opinion.



3. I bought 6th edition of this book more than 10 years ago. But the cover of 6th edition has no photograph, it has an pink color. I think this book has cover useful basic of engineering mathematic. But the explanation is very short and difficult to understand. Lucky enough I use this textbook when I was 2nd undergraduate engineering student in which cover topic about Fourier Analysis, Laplace Transform and Numerical Analysis. Until today, I want to analyze intermodulation distortion of fully differential amplifier but I found that the chapters on Fourier Transform and Laplace transform don't have enough basic to take inverse Transform of exact transfer function. Because it has very high order polynomial. It is very useful for me to see examples of realistic harmonic distortion analysis
   of fully differential amplifier in the 10th edition. But I think this book is good enough to use as a reference because there are not many books which covers all of the important topics of mathematic in electrical engineering



4. I have not purchased many study guides/solutions manuals in the past, but this one has to rank among the worst. First off, there is no study guide in this thing. It has the chapters broken down by sections, but there is not really any information to augment what is in the textbook. It simply goes right into solutions for the problems at the end of each section. Although I would prefer to have a study guide supplement to the text (since that is what I payed for and thought I was getting), I have to say that I would be okay with just the solutions if they were all actually there. But no, that is not the case. Only solutions to selected problems are given, and from what I have seen there is only one solution provided for a given type of problem. This is aggravating, because some problems may be of a similar type but different difficulty level. Making matters worse, only solutions to odd numbered problems are provided. I understand that the authors probably did this to prevent students from buying the solutions to homework problems, since many professors like to assign even problems because there is no answer provided in the textbook. However, since you can usually figure out how to solve a problem if you know what answer you are working towards (hence the reason for professors assigning even numbered problems), having solutions to selected odd numberd problems is just not that helpful. So, I have decided that this thing is useless and a complete waste of money. Don't buy it!



5. This is one of the worst books I have ever used. The examples given in the book are not explained so unless you are the teacher or have prior knowledge to the subject matter you are just lost. I find myself using google for help more than this book.

No comments about Geometry For Dummies (For Dummies (Math & Science)).

5 comments about How to Ace Calculus: The Streetwise Guide (How to Ace).

1. Ok, I'm the type of person that likes to hold onto my old math books for future reference because we all tend to forget some mathematical concepts and equations as time goes on. This book is amazing. After having previously buying a disappointing DVD on Calculus, I had to find another source to supplement, and cover the ideas of Calculus. I found this book was extremely easy to reader and covers all concepts that you are likely to run into in your Calculus 1 and 2 classes. And best part is this book is very cheap compare to others out there yet it has concise and humorous explanations. I enjoy this book so much that it almost doesn't feel much like studying when reading it, yet I am better able to understand Calculus after each section. This book is definitely a keeper and maybe I'll even sell back my Calculus 1 and 2 textbooks to get some of my college money back. Good luck in your Calculus adventure.



2. ...given the mostly glowing reviews. Don't expect miracles from this guide. Nothing particularly enlightening in its contents, if you had stayed awake during classes....



3. I teach Calculus at the high school level and was very impressed with this book. I recommend it for my students as a supplement. It explains the concepts in "real words" and helps some of them understand. Also, additional examples that are well explained.



4. This book really makes me want to learn Calculus 2.After reading it, I find myself going back to my Calculus textbook for a deeper understanding. The explanations are very clear, humorous and to the point. I even ordered their "How to ace the rest of Calculus". I like the way they explain the derivative as being the slope of the tangent line. I enjoyed that book and I recommend it to anyone who may still hesitate to take a Calculus class.. Bravo!



5. This is horrible it doesn't explain the answers in a step by step process. It is good for summaries of chapters in a high school or college level calculus book .

5 comments about Algebra Survival Guide: a Conversational Guide for the Thoroughly Befuddled.

1. Let me first admit that I am no math whiz, and unfortunately I passed my numerically-challenged genes on to my daughter. She has always struggled in math, and I haven't been able to help her much as the math has gotten harder.
   
   So I was really dreading it when my daughter had to take algebra this past year. I still have the emotional scars from hiding under my desk to avoid Mr. Wentworth calling on me!
   
   A friend told me about the Algebra Survival Guide, and I got it and the accompanying Algebra Survival Guide Workbook. This has to be one of the best book purchases I've ever made.
   
   We pulled out the Survival Guide at the start of the year, and used it alongside my daughter's textbook. Right from the start this book calmed down my daughter's anxiety with its humor and funny illustrations. But even more, it helped her -- and me -- grasp algebra with ease.
   
   The book uses a Q&A approach, so first my daughter reads a question about algebra, and then reads the answer. Somehow this format makes the whole process more fun. The book has great explanations, and then examples showing how to work the problems. We did the examples, and soon my daughter was getting a solid B in the class, and enjoying it, too. As I started reading the book and actually helping my daughter, too, her grade actually went up to an A-, and it stayed there all year long.
   
   If you have a child who will be taking algebra, I can't recommend this book enough. My only regret: I sure wish I'd had it when I was in Mr. Wentworth's class.



2. This books gives a good, simplified review of many algebra concepts that are often forgotten once we leave college. It has a simple presentation with a few examples. If you want more practice, you need to purchase the workbook in conjunction with this text. I used both to teach a student who is instructed in the home but I supplemented with other materials. As a special educator, I can say I think a learning disabled student who is taking algebra would find this helpful.



3. My child had to complete a homework packet over the summer to prepare him for his Algebra 1 class. This book was very helpful!



4. Because of the Algebra Survival Guide I no longer panicked when my husband was unavailable to help our 7th grade son with Algebra homework. At first we would read the book together and apply it to his assignment. Eventually, he independently referred to the book, not just for homework, but to supplement his math text (he said the schoolbook didn't explain concepts as clearly). And I have to admit, more than once after homework had been put away, you could find me still reading the ASG. I was surprised at how interesting it was, who knew Algebra could be kind of fun? Algebra Survival Guide: a Conversational Guide for the Thoroughly Befuddled



5. The Algebra Survival Guide is a good book. I'm not sure how to say this, but you can understand it and most math books are impossible to understand." David Bortz, sophomore in honors math

5 comments about Statistics, 4th Edition.

1. I generally agree with what others are saying. What's so unique about this book is that... get this: you'll get one of those rare math textbooks that are *fun* to read. Well... in a nerdy sense. I wish it was updated more recently though, because most of the samples use data back from 70s or early 90s at best, which, of course, does not make the book less correct or helpful.
   
   I am re-learning some of my school classes (graduated with BS in Applied Math in 98) and I wish I saw this book when I took statistics back in college.



2. Many introductory statistics texts suffer from one of two ailments. Either they incorporate too much mathematics for non-statisticians or they provide oversimplified and sometimes incorrect explanations. This text is excellent and is favored by many statisticians who teach the introductory service course for non-statistics majors. The book provides excellent and insightful explanations. It is written by well-known Berkeley statisticians with great theoretical and applied experience, so it is not oversimplified or inaccurate. On the other hand Friedman and his co-authors took pains to minimize the necessary mathematics. It covers all the topics one would want to include in a first course. Real examples are used throughout to illustrate the value of the methods. These include clinical trials and observational studies, telephone surveys and opinion polls and some models in genetics.
   Discussion of the data snooping issue is important, particularly as we move into an age where data mining is now feasible with current computing power.



3. A famous edition of an old standard for stats and I gave this to someone as a gift but knew of it and was told by him that it is still one of the best books on the subject matter.



4. After having progressed through the first 11 chapters of this text, I feel that this text has easily become one of my favorites.
   
   The text uses various real-life case studies (some examples that come to mind are height and weight, IQ, and drug studies) that it will revisit throughout the text. They are, more often than not, interesting and help underscore the practicality of statistics. You cannot go more than several paragraphs without getting involved in a case study.
   
   Although this text is not math-intensive, it does foster something much more useful than an understanding of mathematical equations; it teaches you to think critically about the information that is presented and the questions that are asked of you. To be able to think critically and understand statistics is of the utmost importance, as everyday statistics is, in some way or another, used to justify something. Statistics can be a dangerous tool, and if you don't have a good knowledge of statistics, you may become of a victim of it; the book clearly highlights this fact with examples such as the NFIP vaccination studies, the use of ecological correlations commonly used in political science and sociology, and various observational studies.
   
   If you want math and nothing but math, do not buy this book.
   
   If you want an engaging text with practical examples that will help you to think critically about not only statistics, but also about information in general, I would strongly suggest purchasing this text.
   
   I would also suggest purchasing this item if you want a text that will help you understand the "why" of statistics, not just the "how".



5. No clear examples.
   Unfocused style.
   Celebration of ignorance.
   Overpriced at 0.01+shipping.

5 comments about The R Book.

1. Statisticians like author Crawley bring their data in Excel spreadsheets,
   and want spreadsheet outputs. They may be happy with this book. Others
   bring their data from C or Fortran programs, and need an .eps file output
   in order to get their graphics-containing manuscript reviewed. They will
   find this book completely inadequate. The lack of figure numbers shows
   little concern for the reader. Missing: sprintf, gsview, .eps files,
   dev.off, ... . R's Unix-like "man" pages do help. There may be 5-15
   poorly-explained options, and one example for all the options. Thus, the
   "man" pages are inadequate backup for a book of this title. There are
   variations in the singlar value decomposition of a matrix, depending upon
   whether the Sigma matrix is square. Crawley omits such details.



2. The graduate student as well as PhD researchers and Industry consultants are often faced with learning programs in double quick time and need references which are clear, concise, and have numerous worked out examples of how the program works. Furthermore it is often a daunting task not only to search the web for references, help, and worked out examples but searching through the numerous available books on the subject "using R."
   
   I took a wild stab on this title from an advertisement I received from Wiley. In my opinion this text is not only has a great introduction to the essentials of the R language but a well rounded amount of information for nearly all foreseeable tasks I would be using R for.
   
   To put it short, the title should be called "De 'ARGGHH!!!'ing R"



3. Given the length of this book, and the list of contents covered, I had the highest expectations about it.
   
   After spending 2 intensive months reading it, I have mixed feelings. Positive points are the large number of statistical models and methods described. The R examples are useful to follow the explanations, and the writing style is comprehensive. I agree with some reviewers in that the linear models section (Chaps. 9-19) is the most useful one. The last Chapter also presents useful tricks for dealing with graphs in R.
   
   Unfortunately, I have 2 important complaints. The first one is about the presentation of contents: simply CHAOTIC. The author systematically abuses of cross-references. You will find sentences like "here we present an example of [method XX] that will be introduced on page XXX" throughout the entire book. This is disappointing, since it forces the reader to constantly move back and forth, looking for the relevant info. There is no point in presenting an example based on a method that you haven't introduced yet. Examples should be autonomous, and not frequently taken from previous data sets "already used in page YYY".
   
   The second complaint derives from the previous one. The book is hard to use as both a reference manual and a companion for undergraduate or graduate students. Disregarding the comments from the author, if you don't have a solid theoretical background in statistical inference, regression analysis and linear models, you won't get very much benefit of this book. The author completely lacks of a rigorous, structured method for presenting new concepts. Even worse, important definitions and concepts are usually hidden in between of examples that has nothing to do with them.
   
   In summary, if you already have a good theoretical background in statistics, this could be a useful add-on to your bookshelf (though be ready to spend a lot of side tags to map important concepts for later).
   
   If you're looking for a introductory book with R, Springer has just published a second, expanded edition of the classic book by Dalgaard. If you're looking for a definitive reference manual of statistical methods illustrated with R, you will have to wait for something else, or look for specific titles (Like Faraway's "Linear Models with R"). For Ph.D. students looking for a comprehensive an up-to-date book on statistics with R, to improve their skills quickly, I still recommend the second edition of "Data Analysis and Graphics Using R", by Maindonald and Brown.



4. This book is an excellent introduction to the R language and the statistical theory underlying it. It requires some patience as there is a considerable deal of repetition (the exercises are all very similar but gradually increase in complexity as one progresses from two way anova to generalized additive models and more). Also there are a few small errors (I did not mind these as they helped me realized that I was still concentrating) - the book could have used a keen editorial eye. Am very happy with my purchase.



5. This is a good book, if you are a lousy programmer and just want something to get you started in R. And that was me a couple of months ago.The style is conversational, the exposition patient. That's just what you need if you have been put off by the on-line documentation.
   
   In its overall architecture, the book is a bit scatty. It spends a little too much time on statistical theory and, as other reviewers have said, not enough on the more advanced programming features of R.
   
   But if you just want something to help you take those first few steps, you really can't go wrong with this, and it will remain a great reference for the basic functionality. Expect that at some stage will have to supplement this with material that iscloser to your specific interests, and you won't be disappointed.

5 comments about Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart.

1. Ayres demonstrates how statistical analysis of large datasets is affecting the way the world works in a broad range of applications: credit card companies, sports teams, wine critics, development economists, medical practitioners,* law enforcement agencies, schools, etc. "Freakonomics didn't talk much about the extent to which quantitative analysis is impacting real-world decisions. In contrast, this book is about just that - the impact of number crunching" (p13).
   
   As an economist, some of the work is familiar (for example, the research Ayres and Steve Levitt did on the value of the vehicle-recovery device LoJack or the Poverty Action Lab), but Ayres gives a good introduction for the uninitiated. And he covers such a broad range of applications that I learned a great deal.
   
   Like other research surveys (Freakonomics, The Tipping Point, Blink, Stumbling on Happiness), I view these books mostly as surveys of interesting research. Each has a central thesis (Ayres' is that traditional intuition and expertise will be - or already has been - replaced by computing power and will have to learn to complement that power rather than compete with it) which may or may not be convincing, but the books tend to be good rides because so much of the surveyed research is interesting. (For example, I'll be studying more about Direct Instruction - a scripted way of teaching reading that may be useful in my own work - based on this book; and the model Ayres expounds of how private firms learn from iterative experimental trials may apply well to some of the agencies I engage.)
   
   As far as Ayres' thesis goes, I find him relatively convincing (computers with lots of data do predict many things better than people**) but despite his many caveats, the tone should probably have been more humble. He doesn't - for example - explore the issues brought by Taleb in The Black Swan: The Impact of the Highly Improbable, how traditional statistics may be worse than useless in financial markets where a single, completely unpredictable bad shock can wipe out years of carefully predicted investments.
   
   This book was lots of fun to listen to, not least (unintentionally) because Ayres loves giving irrelevant but amusing descriptions of his researchers. The examples below are all economists:
   
   "Ashenfelter is a tall man with a bushy mane of white hair and a booming, friendly voice... No milquetoast he" (p2).
   
   "Even now, in his forties, Larry [Katz] still looks more like a wiry teenage than a chaired Harvard professor (which he actually is)" (p65).
   
   "Esther [Duflo] has endless energy. A wiry mountain climber..." (p73).
   
   And of course you know this is the Freakonomics family because of the Levitt-love scattered here and there: "There is a new breed of innovative Super Crunchers - people like Steve Levitt - who toggle between their intuitions and number crunching to see farther than either intuitivists or gearheads ever could before" (p17).
   
   I listened the unabridged audiobook narrated by Michael Kramer (not Michael Kremer - quoted in this book on p74), published by Books on Tape (6 CDs). Kramer does a good job except when he tries an Australian or British accent.
   
   * For an excellently written description of evidence-based medicine and more, read Atul Gawande's Better: A Surgeon's Notes on Performance.
   
   ** One of the most striking findings comes from the meta-analysis (1996) of two psychologists, Meehl & Grove, who look at 136 studies comparing human judgment to equation-based judgment. In only 8 of the 136 studies was expert prediction found to be appreciably more accurate than statistical prediction." Overall, experts got the predictions right 66% of the time whereas Super Crunchers got them right 73% of the time. And the 8 in which experts did better weren't concentrated in any particular field. From looking at the paper myself, I found that 64 of the studies favored the Super Crunchers whereas 64 found the two methods roughly equal. Noteworthy. [In the book, p111 and p232.]



2. It comes on the heals of some really great non-fiction analytical books. Unfortunately, this book is all anecdotal and lacks real substance. It is good for non-mathematical, non-analytical people, but not good for people with solid educations in math, statistics, and data analysis.



3. This is new? The notion that empirical research is useful has been dealt with in book after book. The book not only recycles stories word for word without quote marks from the New York Times and other publications. There are hundreds of books that show that empirical work can help understand the world. What is new? What is interesting that is new here?



4. The answer is of course: a lot.
   And Ian Ayres' book will tell you a little about it.
   
   Supercrunchers are those who use lage datasets
   to find patterns in human behaviour, and
   predict the future based on these large datasets.
   
   The book informs us that super crunching is on the verge of being
   used all over. E.g.
   Chess grandmaster Kasparov was no match
   for IBMs Deep Blue chess computer,
   that stored some 700.000 grandmaster chess games to help find the
   winning move.
   The IRS could use its data to tell a small business,
   if it is spending too much or too little on advertising.
   Indeed, the IRS probably has enough data to
   make good estimates on whether business, marriages, etc. etc.
   will fail - based only on comparison with its existing dataset.
   
   For the paranoid, it is a horror that supermarkets could map your life cycle and predict your next purchases pretty accurately (based on
   what other similar customers did).
   For the optimist data mining is a good thing and we'll all lead better lives because of it.
   
   Want to write a bestseller about it? Compare your title and some key words with data from a database of books, titlescore.com, containing millions of bestsellers and flops, and you will get your answer.
   
   It all seems pretty straight forward, and the book has some nice examples of what we can expect in the coming years.
   
   -Simon



5. 
   This is an easy and mostly entertaining read. The author uses many anecdotes to
   persuade us that statistics can be a useful tool for decision making. Some of
   the described applications use lots of data and multiple regression. Those are
   easier to do now than they used to be, because more data is collected and kept.
   Some are trivial. If your company hurts a customer, apologize. You might get
   some ideas of thing to do that might help your organization. You will not get
   any detailed help about how to implement the improvement, but there is a good
   chance there is enough information that some systems person can figure out what
   other skills are needed to make the idea work.
   
   There is some discussion of limitations on the methods, and some warnings about
   potential abuse, but not enough. Ayres seems to confuse correlation with causation.
   He also frequently assumes the sample is representative of the population.
   Even when trying to make the sample representative, it often is not. He also
   assumes the answer is in the data. Sometimes it is not. Ayres reports a study
   concluding widespread point shaving in college basketball because a distribution
   at game end did not match the distribution five minutes earlier when a highly
   favored team was ahead by about the spread. I have no opinion about the conclusion,
   but the simpler explanation of the coach thinking it was late enough to safely
   let the weaker players participate more was not considered.
   
   Regression is a powerful tool, but it is easy to misuse. For an ongoing
   survey of misuses, see junkfoodscience dot com, a blog. Many of the entries show
   the flaws in statistical claims of medical trials. Also try stats dot org.