5 comments about At the Crest of the Tidal Wave.

1. Having read this book, as well as Ravi Batra's "Crash of the Millenium" and James Dale Davidson's "The Sovereign Individual", I can't help but point out that these are the same people that were telling us to expect a U.S.economic/financial market collapse throughout the '90s(see: "Blood in the Streets" and "The Great Reckoning" by Davidson/Rees-Mogg, "The Great Depression of 1990" by Batra, and Prechter's newsletters/special reports from that period). Obviously, they turned out to be just a tad off the mark. After a peruse of this material, have a look at one of Harry Dent's books for a look at the baby boom spending wave that continues through the latter half of this decade (Dent points out on his website that the current economic dip we are in is similar to the one that took place between 1920-1922, before the Roaring 20's market took off). The only way that the kind of boom the Spending Wave projects can ever take place would be if the majority are looking in the wrong direction. Material such as this book from Prechter, as well as Batra and Davidson, will do very nicely.



2. This book is a must read for financial survival. Prechter has an engaging writing style. His opinions are often outrageous and sometimes too extreme. This value of this book is in that it is so different from the conventional financial press.

   Almost alone Prechter predicted the great bull market back in 1979. He then called the top prematurely but at least he did warn this readers that a top was coming. The scope of Prechter's vision is awesome. He has charts with trendlines going back to 1700 with projections for the next century.

   Chapter 11 "Manifestations of Investor Psychology" is very powerful.




3. There was a movie which showed an approaching tidal wave. There was no noise because the wave was travelling faster than the speed of sound. This is the case of the oncoming financial tidal wave of disaster. One can hear the bullish rantings of a stream of advisors, nudging us into a sleeping wonderment of good things to come. The tidal wave is on its way. Prechter has pointed out the various items unfolding before our eyes. He was early in many of the prognostications, but they are surely falling into place. If you read the book, you will surely see how they are unfolding. Your financial health is at stake. The tech wreck was only the beginning. Read on, there is still time, but the book will be out of date in a couple of years.



4. I bought this book used about three years ago. Although I was skeptical of it's contents, since the title seemed dated, I picked it up because it was cheap. It was one of the best buys I've made.
   
   Although I did not read the entire book, the portions I did read (chapters 9-12 about investor psychology) were timeless and made the book well worth the buy. Those chapters are highly recommended reading for contrarians. I'll quote among my favorite lines: "They show that people view stocks as being less risky than treasury bills. Indeed, article after article refers to the "risk of missing gains" as being more important than the risk of loss. This is an optimism so extreme that it has not been seen in the West for nearly three centuries." (p154); "The public is always trading oriented in the early stages of a bull market, and "investment" oriented at the top. - One-Way Pockets 1917 (189); "No top-heavy market with public involvement fails in the end to punish the average investor for his gullibility." (190); "All investment is speculation, and there is no more risky speculation than one that is confidently viewed by a majority of portfolio managers and the public as an investment." (414).
   
   I gave four stars because Prechter's timing of the coming crisis was way off and his predictions sounded extreme, for example: chapter 21, page 431, "... secessionist movement will take place in many countries, including the US ...one or both current political parties will dissapear ...unemployment will reach 30%."
   
   Overall I highly recommend this book. Tidal Wave is easy to read and follow.



5. If you go to the list showing all of my reviews, you will see that I have read quite a few books about the stock market and trading in general. While I have encountered information that talked in generalities about the Elliott Wave Principle, I had never delved into it in much detail as I never felt the methodology was consistent. Having trudged my way through this book, I have come to the conclusion that either (1) I am too stupid to be able to understand and trade based on the EWP (an admittedly distinct possibility), or (2) I have never read so much after-the-fact 'curve fitting' in my life. If you are a student and believer in the Elliott Wave Principle, this will be like adding a second Bible to your collection. If, however, you don't already know and understand the EWP, and unless you are a genius, plan on spending years trying to understand the theory before you will be able to implement it into your trading system. Sorry, Mr. Prechter, but I just don't get it.

2 comments about Business Statistics: For Contemporary Decision Making.

1. Good economics book. Could use more real-world examples.
   The book arrived in good condition but did not include the CD that would have been there had I purchased it from a brick and mortar book store.



2. Very good book for business majors taking a statistics class. Statistics is not easy to understand, but this book tries to make it as painless as possible. The flow is easy to follow and the examples make it all the more understandable.

5 comments about Making Sense of Statistics: A Conceptual Overview.

1. Clearly, this is an introductory book. As the title implies, the book's contents are very basic - most appropriate for undergraduate (or maybe even high school) statistics; probably not for graduate students unless they need something for a 'super quick' review. (But even then, there are references other than this book better suited for that purpose.)
   
   The author says the book might be used to demonstrate "that the interpretation of data is not always straigthforward" (p. vii). But I think using "excerpts" of studies makes it more difficult to understand how and why approaches to data interpretation vary. An appropriately chosen article may serve the purpose as adequately as the book (if not more).



2. While this book does conform to the title segment "A Conceptual Overview", I am not sure that it satisfies an existing market niche. I have been teaching basic statistics at the college level for decades and am used to equations and formulas in a statistics book. Therefore, I will admit that my background may be causing some bias in my outlook.
   There is only one formula in this book, the expression for standard deviation and it is in an appendix. And unfortunately, it is not well presented; the sigma notation is used without being well explained. The coverage is thorough; all of the topics that I cover in my basic statistics class are in this book. But covered in such a superficial manner that I find it difficult to believe that the reader will really be learning anything about what statistics really is. I don't see how it is possible to really learn what a mean is without seeing it in formula form.
   The only people that I could possibly recommend this book to would be those who have no idea at all what statistics is and what it is used for. Other than that, there seems no other place where it can be used.



3. This book is primarily designed for psychology and other social sciences students, so that they can understand the statistical information in reports, etc., that they may read. It is based on two premises: (1) that a little knowledge is a good thing, and therefore the smaller the knowledge, the better the results; (2) that the best and more significant learning takes place without any 'doing' component; simply reading the text is enough.
   
   Unfortunately, the book calms the unknowning reader into a false sense of security. A very common phrase in the book is "this is beyond the scope of this book," and this is used to dismiss even simple extensions and all calculation. The examples used are trivial and simplified, because anything more might require a calculator and some understanding. The reader is led through some interesting areas of descriptive and inferential statistics, but unless they go somewhere else, they won't learn anything of any significant value. Some terms are used that in proper statistics are now either outdated or given alternative names, but nothing seems to back them up. For example, Gosset and the t test are mentioned, but the common statistical appelation of "Student's t test" is not. ANOVA is introduced, but not how to get the results, nor (really) how to interpret them.
   
   The second premise is perhaps the worst. Unless a student actually crunches some numbers, they will never appreciate how these things work, and in particular the risk of errors by the user. Too much statistical analysis today seems to depend on stuffing all the data into a package, such as SPSS, and looking at the print-out, and only applying some thinking at that point, rather than at the experiemental design, data collection and data entry stages. This book supports this approach in the reader.
   
   If people today are scared of numbers, especially quantities of numbers, surely giving them the tools to deal with those numbers and make sense of them through understanding them is the preferred solution, not the analgesia of non-thinking that characterizes this book. If they were in the engineering or physical sciences, tools and understanding would be the solution adopted. Why is this not the case in the social sciences? Is EVERYONE in these fields both ignorant and terrified of statistics, and numbers in general?
   
   The entire design and philosophy of this book is back-to-front and ultimately counter-productive to the education of people who can actually make sense of statistics. It smooths the pillow of the dying intellect and promises a better life in the next world. It breeds a group of people who drive statistics packages without understanding statistics, while feeling that, somehow, they actually do. It makes the statistical impoverishment of researchers in the social sciences more certain, rather than less.
   
   Because there is no significant level of mathematics involved, readers must learn terminology, rather than what's happening with the data. Instead of an understanding of the fundamentals, the reader learns to identify different statistics and their symbols, different sampling methods by name, etc., but there are no logical connections made, no sense of what statistics is really about in this field. To add to the student's difficulties with a terminology/definitions-based learning strategy, there is no index in this book!
   
   The ideal book for meeting the need for basic statistical understanding is Darrel Huff's "How to Lie with Statistics", which is basic, comprehensive, sceptical and almost devoid of calculation. It actually serves to increase statistical literacy at a basic level, and does not try to extend itself beyond dealing with basic descriptive and inferential statistical problems.
   
   While Huff's book is great for a sceptical analysis at a general level, such as a technical report or paper's conclusions, unfortunately it is of little use in trying to analyze the details of the statistics spewed out in those reports and papers in the social sciences. Pryczak's book attempts to deal with this, but fails miserably on all counts. Readers have no overview, despite the title, of the bigger issues or the need for scepticism and common sense. The explanations are too comfortable and comforting to suggest scepticism of statistical analysis. Readers have no means of accessing the meaning of the statistics, because there is no attempt to deal with real data. Readers never have to DO anything, beyond read the text and look at trivial, doctored examples. The book presents no help whatsoever to a student in a course where even basic statistics have to be derived from some data, e.g., using Excel and its Data Analysis add-in package.
   
   While Huff spends some time on a rigorous interpretation of 'average,' Pyrczak cannot even manage this without waffling, and fails to explain how to calculate a mean, median or mode ("it will be all right, don't be frightened, the horrid statistics won't hurt you, be calm, trust the software package or the other person to get it right, it will be all right"). A formula for the standard deviation is tucked in an appendix. Pyrczak gets into a tangle over standard deviations and standard errors, not being clear about either, really. And from here things go downhill, but the comfortable, comforting tone remains ("In know, statistics is SO hard, but this will allow you to forget all that and feel OK again. You won't be challenged by it if you don't want to be (and who would ever WANT to try to actually understand statistics?).").
   
   In summary, this book is a waste of ANY student's time and money. It is unfortunate that it is a required text in some courses, but that fact probably explains more about the statistical weaknesses in the social sciences than anything else (r^2 > 0.9). This book is actually counter-productive to education in statistics.
   
   Recommendations: (1) If it's a required text in a course you are taking, I pity you. Get a proper statistics text so that you can actually learn something useful.
   (2) If you are thinking about using this as a text in a course you are offering, actually look at the book. If you think it's good and useful, get someone else to run your course--your course will not help anyone's statistical understanding (including yours); in fact it will do quite the opposite, without anyone realizing it.
   (3) If you are simply interested in learning about statistics, don't even consider this book.
   (4) Amazon needs negative star ratings, as this would be about -3 (90% CI of 0.1).



4. This is a case of a publisher who puts out different editions without thinking. It difficult (and very expensive)to get all of my students to purchase the same Edition. In fact the latest edition is almost impossible to locate. Yet, the workbook pages are so varied from edition to edition, that it is nearly impossible to coordinate among students in a class. While I applaud Holcomb for wishing to keep the examples fresh and updated, this is a case of simply not thinking about how the book would be used. I would suggest staying away ... its more trouble than its worth.



5. expensive for a paperback but I guess it is in high demand. Book was in very good shape. Shipping was average in speed.

5 comments about Multivariate Statistical Analysis: A Conceptual Introduction.

1. Covers fundamental concepts and probability in the first two chapters; then proceeds to full discussions of correlation, regression, and analysis of variance, with shorter discussions of more advanced topics: discriminant analysis, factor analysis, cluster analysis, and multidimensional scaling. The emphasis is less on math and more on concepts and uses than with standard textbooks. This book made clear several concepts that I had tripped over in The Cartoon Guide to Statistics.



2. This small book it's a good way for experiencing in multiv. stat. analysis. It's very understandable and easy to read.



3. I am enrolled in a Risk Management course. Without any previous statistics courses I was struggling. My professor recommended this book and it changed everything for me. I was actually able to learn and understand statistics from the beginning to multivariate analysis from this book. It made it so very plain and simple. I am now successfully going forward again. I would recommend this to anyone from beginner to Masters level who needs a reference at hand.



4. As a statistics software trainer, most folks that I meet are not looking for a book that explains how to use a method by hand, without the computer. Unfortunately almost all the books you will find on Multivariate Stats will be very large tomes bloated with formulas and exercises. This book in contrast is: 1) an easy read; 2) focusing on the concepts behind the technique; 3) is reasonably priced; and 4) is not a door stopper. Check out the table of contents. You will probably find the technique you need. Factor Analysis, Cluster Analysis, etc. are all represented. If you are an SPSS user, as I am, you won't find any pictures of SPSS, or step by step instructions. You will find only the theory behind the techniques, but there is more than enough great content here to warrant adding it to your library. Not only that, most step by step guides skimp on the theory, so it is best that you get one of each. Check out Norusis for good books for "step by step" in SPSS. She also does a good job at the theory, but Kachigan gets the highest grade for explaining theory.



5. well worth every penny or cent.
   
   clear examples on the nuts and bolts of statistical modelling.
   
   highly recommended for the beginner to the expert to fill in the gaps in statistics.

No comments about Multilevel and Longitudinal Modeling Using Stata, Second Edition.

5 comments about Quantitative Methods for Business (with Crystal Ball Pro 2000 v7.1, CD-ROM, and InfoTrac ).

1. This book is written in unnecessarily complicated language and does not present information in a way that is easily understood. I teach graduate courses in quantitative methods and I made the mistake of ordering this book for one of my courses without reading it first. It was a disaster!
   
   Unless you are getting a doctorate and need to know lots of complicated formulas without adequate explanations, DO NOT buy this book.



2. I am a professor and have used this book for several years in my undergraduate quantitative methods course. The book is quite clear and easy to teach from. I have had very few complaints about it from my students. The book covers the important quantitative methods that an undergraduate business student should know, and uses only the mathematics necessary to present these methods properly. The material in each chapter is correctly presented as useful for managerial decision making. Decision making is the key, and it is ultimately the purpose for businesses to use quantitative methods. The book makes this important point very clear in most chapters. Typically, the book presents one main business problem per chapter, then builds on that problem, showing how to develop the problem solution as the chapter progresses. Once solved, other similar type problems are addressed in some chapters. Not all exercises at the end of the chapters are useful, but most are, and it is simple to pick and choose to get a good set of student problems. The "Quantitative Methods In Action" sections are quite useful to show students how these methods are really used in the business world by real companies. This book is practical, application oriented, requires a minimal amount of mathematics, and is not at all difficult to read and understand. I do not know personally the authors, and I have never had any communication with them, but I would not hesitate to recommend this book to anyone wanting to learn basic quantitative methods. In my opinion, it serves that purpose quite admirably.



3. This is the most terrible textbook I have ever used. It makes the already difficult theory even more difficult, not enough examples and explanation. The exercises are extremely hard.



4. I bought this for 1/3 of the price of the bookstore. Corners were beaten up, but it cost less then buying from bookstore minus what they would buy it back for.



5. Very in-depth.
   
   Most examples are from real corporate situations (though the company names are changed). Definitely a permanent reference guide to add to your book shelf after you complete the class.

5 comments about Statistics for Business and Economics and Student CD (6th Edition).

1. This book bring us statistics in a simple way, begining with easy exercises and increasing them to hard tasks. I have tried a lot of diferent books, some of them in Portuguese, and this was the only one that is realy good enough to teach us without a tutor or professor. It brings the most important parts of statistics for Business and Economics using exercises that talk about real cases and real hypothesis testing. It was easer to learn from this book than to do it in my own language.



2. I used this book for my MBA statistics class recently. This book is very well written in a clear way, not meant to be fancy but to provide a comprehensive coverage of most, if not all, relevant topics. I also belive that the coverage depth of each topic is adequate enough to satisfy all common business and economics applications.



3. I'm an MBA student in a top5 business school in the US, and we use this as our textbook for the basic stats course. I've only read the first 5 chapters so far, and I've found this book to be one of the worst textbooks I've seen since college. Some very simple concepts are explained in very confused (and confusing) language, the text is very arid and skips over most of the conceptual subtleties or fallacies that the unsuspecting user of statistical data may easily fall victim to. I strongly suggest leafing through it before deciding whether to buy it (you can start with chapter 2, which is pretty typical of the tone of the book and, being the 1st "substantial" chapter of the book, doesn't assume knowledge of concepts defined in previous chapters).



4. This book is fairly comprehensive covering all the major topics that a student would need for the statistics modules in various business courses. Managers need to have an understanding of statistics so that they are able to manipulate the numerous masses of data that come their way into meaningful and useful information that they can employ in making business decisions.
   
   The author presented the material in the book in a simple and clear manner without any complicated algebra, making it readable by students in business schools with a basic knowledge of mathematics. The author also provided large numbers of examples and exercises that should assist the reader in consolidating his/her understanding of the concepts described in the book.
   
   Most managers are consumers rather than producers of statistical information. This book equips the reader with the expertise to enable one to be an informed consumer who knows the right questions to ask and the kind of information to request from those who produce the statistical information in the organization.



5. I really have to warn everybody of this book! This book confuses me. This is the prescribed text for my first year subject. Maybe I am not senior enough to give comment on this book. Everytime I read this book, it confuses me somemore! If you have a choice, don't buy this book. If you are really serious in studying and not just buying an expensive book for display, don't ever buy this book.

2 comments about New Introduction to Multiple Time Series Analysis.

1. This book provides a fairly elementary view of the vast subject of time series analysis. It easy to read and the author provides lots of basic calculations. Typically, such books stay away from the cutting edge topics but not this one. It is quite complete. I highly recommend it to anyone that knows a few basic things about time series and wants to take it much further.



2. If you are looking for a book on VARs and cointegration, this is it.
   Very clearly written, and with numerical applications of every new concept (so that you can check the accuracy of your codes ...)
   Its a significantly improved version of the last edition.
   Highly recommended.

5 comments about Statistics for Business & Economics (10th Edition) (MyStatLab Series).

1. First of all I am not a statistics major and although I find statistics to be a very interesting but challenging subject I am afraid to say that so far I have not been very successful .... I need extra help and I have not yet found the solution manual for this textbook and I am amazed at the fact that there isn't one ? Can anyone help me...

   Thanx

   Norma_Zuniga@yahoo.com




2. Often using real-life examples taken from the media, McClave presents materials in an orderly fashion. Sub-sections are small (usually 5-6 pages) and problem sets are very nicely divided into Mechanics, Basic, and Advanced problems. My only dislike was chapter 3 counting rules, which seemed to be added without proper foundation. As both a student and now a tutor of this text, I find McClave's level of explanation sufficent for an introductory text.



3. The seller contacted me promptly after i send him/her a message. The book arrived shortly after the order was placed and was in a great shape.



4. The fact that this book is in its tenth edition is an indication of its popularity. Many years ago I taught courses in business statistics at the advanced undergraduate and first year graduate level in the business school at Cal State Fullerton. I found it to be an excellent text to teach out of at that time. Since many editions have occurred since then and Terry is a third authored introduced in editions after the one I taught out of I really can't give a review of this edition. But I do think it will be helpful to amazon readers to know that McClave and Benson have a very good track record as authors of business statistics texts and Terry Sinich has coauthored a number of successful introductory and intermediate level statistics books. I am confident that this book is well written and has kept up with the advances in time series analysis that affects typical business related statistical problems.



5. I taught out of the 9th edition of this book and I liked it a lot. This is the perfect book for a second course in "methods statistics", i.e. a book about how to do the calculations, when to do them, and what they mean. There are no proofs or derivations, just recipes, but supplied with a lot of worked out examples, and an excellent discussions of when what methods are appropriate.
   
   My gripe with the 10th edition is that the last two chapters, Time Series, and Non-parametric Statistics, are not printed on paper, but only available on the supplied student CD. These are two of the chapters that I teach, and I find it unacceptable that the students will not have these chapters in the book, but will have to look at them on the screen. Or, if they decide to print them out, our department budget for printing and copying will be bancrupted. The publisher's explanation was that this was done "to save printing costs". Yet, the new edition is not any cheaper than the previous one!
   
   Reluctantly, I am switching to an inferior text by a different publisher, just because it has all its chapters printed.

5 comments about Introduction to Time Series and Forecasting.

1. this book is excellent because it provides us with many examples and detailed explanations.



2. In the process of building a website targeted to those good folks that are striving valiantly to make a living through Internet marketing, you might think that an early objective would be to assemble a library of good reference material. After all, if you are planning on providing sensible information to your readers, then you should have a few good text books on hand to refer to when you need to be sure that some little tidbit of information might actually work. Well, at least I did. So, I have been scouring the Internet for textbook on the subject of Forecasting, which we share a common interest in. I have purchased a few and, for the most part, they are really quite informative and will be useful when the time comes. There is, however, an exception to this.
   One book I purchased bears the title "Introduction to Time Series and Forecasting, Brockwell, Peter J and Richard A Davis". Being an intelligent sort of chap, I naturally took the word "Introduction" to mean just that. You know, you've been introduced to people before and becoming introduced usually means that 1. You look at the face. 2. You grasp their hand and shake firmly and 3. You exchange pleasantries, such as "Hello, it's nice to meet you".
   Now, I never blame the person making the introduction if the relationship doesn't work out. After all, it's not their fault that two people hopefully sharing a common interest (after all, why bother making an introduction?) aren't all that compatible. There are likely to be many reasons for the incompatibility, the first of which could be that people travel in different circles and your circle isn't ever going to be part of their circle. Sort of an exclusionary relationship, you might say. And, not to be overly judgmental of others, of course, there may be plenty of good reasons for that. If everyone existed in one social circle, after all, the world would be beyond boring.
   Anyways, the text book is a wonderful creation, that is, if you're a post-graduate or doctoral candidate. Upon opening the cover, expecting to be warmly introduced, I was rather amazed at the depth of equations and formulas gracing practically every page. I felt intimidated immediately. Remember the movie "The Ring"? This had to be rocket science, or more correctly, forecasting science at its most extreme! Wow! I should have really paid more attention during my statistics classes. So, I quickly closed the cover and tried to get a refund from the seller. Note the word Tried here. They didn't want it back either.
   The good Post-Grand and PhD. candidates of the science of forecasting probably don't need an "Introduction" to Time Series and Forecasting. Next time I buy a book, I think I'll look for something with "Sandbox" in the title.
   May all your Forecasts be Good Forecasts at [...]



3. A decent basic introduction covering a lot of topics. It's much more accessible for learning the subject for the first time then many other books which pile on the mathematical notation and obscure the actual meaning of things. The accompanying CD is very nice, although it gets annoying very fast that you're restricted to very small dataset sizes---but it does help in learning. The only two things that are somewhat of a problem with this book are 1) many times, rather than clearly stating "here's the algorithm you need to implement", you are referred to 3 or 4 other sections of the book for pieces of the algorithm, often without a clear explanation of exactly how that earlier section is supposed to be worked into the current desired algorithm and 2) there aren't a lot of practical insights as to how to actually initialize many of the algorithms (everything is great if you already know all the parameters in advance but starting from scratch with just raw data isn't dealt with I think as fully as would be useful). All in all, though, the book is helpful and, as I said, very good for learning the essential concepts for the first time.



4. In contrast to their graduate text "Time Series: Theory and Methods" this book is more elementary and introductory and is pitched at the advanced undergraduate level requiring only calculus, elementary statistics and matrix algebra. It gives very good coverage to a wide variety of time series models and includes some nonstationary models. In this second edition the chapter on nonstationary models includes the latest coverage of ARCH and GARCH models presented in a way that I found very accessible.
   Computations are done with ITSM and in this edition the ITSM 2000 version 7.0 edition is included on a CD so that students can reproduce the authors' calculations and run analyses of their own.
   
   Another nice feature of the text that distinguishes it from other texts at this level is the introduction of multivariate time series, coverage of state space models, chaos and cointegration. Ideas are illustrated with examples. Important theory is discussed but is kept brief and theorems and proofs are not given to the extent of their other more theoretical text.



5. The term 'introduction' is odd for a book bristling with mathematical symbols. Some academics don't always understand that people without mathematical training still need to use concepts taught in universities.
   
   This book is excellent if you've had that training and want to expand your knowledge. It's really an introduction at the top floor of the learning edifice, not the front entrance!
   
   More positively, the software that comes with it is excellent. The examples are clear enough and you can bypass a lot of the deeper mathematics by letting the program suggest the best models. But the only way to get the full benefit of it is to understand the accompanying discussion. This I tried to do by looking in other books (and the WWW) for a more straightforward approach directed at 'dummies'.
   
   For an introduction to the complex area of time series analysis a lot less maths would have made this book much more readable. But I will keep at it.