Customer Reviews:
Showing reviews 1-5 of 21
 Entertaining and educational November 15, 2009
rbnn (Berkeley, CA United States)
Outline of statistical methodology, targeted at business people. Strong emphasis on hands-on application of sophisticated techniques and nonparametric analysis.
At first I was almost offended by the author's assumption that its readers didn't know or understand basic math, and that, in this instance, they should even be running simulations. And I did find the whole "business-speak" tone (everything's friendly, jocular, simple) a bit annoying, never really liking that culture. But after a while I began to appreciate and understand the author's outlook, and I felt I even learned some fresh ways of looking at things.
The book has a lot of stories, and emphasizes human relationships a great deal. A lot of mildly entertaining pictures.
Excellent description, or at least reference, to Simpson's paradox (the clearest I've seen, in fact - comparing Jeter's and Justice's batting averages from 1995-1997 turns out to be an example: Justice has the higher BA for each year, but Jeter has the higher cumulative one).
Good, clear discussion of Jensen's inequality and, more important, why it matters!
Although it's true there is a lot in the book about one particular fallacy people make, confusing an average with a distribution, the book is more than that. It's a really good way I think to interest people in statistics and to introduce them into thinking rigorously. I learned some really interesting stuff about finance, which I had not known, for example. And where a more rigorous treatment is required, there are plenty out there.
So all in all, I think my first reaction was incorrect. This is a very good book: it's interesting, it's fun-to-read, it has some information that nearly anyone would enjoy, and it's a good starting place to get an idea of what some of the key problems in statistical inference are. I've already recommended it to several friends, and I highly recommend it to others as well.
 Useful explanations lost in hype November 11, 2009
David J. Aldous (Alameda, CA USA)
Unusual style, intermediate between a serious attempt to explain a simple yet important statistical idea in plain words and graphics, and the frothy "management secrets" style that permeates the Business section of an airport bookstore, the latter reflected in breezy writing, a layout of short chapters containing short sections, and the admirably inexpensive price. The idea can be said in 5 words -- "don't put averages into spreadsheets" -- where averages refer to expectations about the future. A typical illustration is what Operations Research calls the Newsboy Problem, which supposes you buy the daily paper wholesale, sell retail, but are stuck with any unsold copies. If you sold exactly 100 copies every day then you would simply order 100 copies; if your sales vary but average 100 a day, then the best number to order is (typically) not exactly 100, because of asymmetry between profit on sold copies and opportunity cost of lost sales if you run out. In such simple settings the idea is rather obvious, but now imagine some business spreadsheet, with actual figures from last year which combine in some complicated way to get last year's actual profit. It's natural to try to estimate next year's profit by entering estimates of each line entry and having the spreadsheet recalculate; but in any complicated setting there are always asymmetries between upside and downside and one does not get the correct "average profit" so easily. And one is interested not only in averages but also in risks of large losses.
This is no mystery to statisticians, just one of 100 workaday concepts not particularly emphasized in a typical college statistics course -- though as the book implies, worthy of more emphasis in a business statistics course. Scattered through the book are the components of a potentially great 30-page chapter illuminating this idea via graphical ideas of representing distributions as histograms, and describing contexts where asymmetries are important. For instance: bonuses for meeting a target, inventory and supply-demand, options, a project takes as long as its longest component, and interesting analogs with portfolio theory.
It would have been valuable to extend these 30 pages to either (i) in depth case studies, or (ii) a wide-ranging book explaining 10 different statistics ideas in 10 chapters. But instead, this book becomes a mashup of historical and personal anecdotes, superficial descriptions of case studies, some of the "popular science" style topics in probability and statistics covered in many other books, and witticisms about traditional mathematical statistics as "Steam Era statistics". As the author implies, it would be useful if Excel and open source analogs had an option for entering distributions instead of numbers. Alas, this book turns into a plug for the author's Probability Management software, and case studies turn into one paragraph testimonials.
 For someone who want to be miss-informed about statistics October 15, 2009
D. Benachenhou (washington, dc USA)
3 out of 11 found this review helpful
The author appears to have little knowledge of statistics.
1. There is a whole part of statistics called Non-Parametric statistics which overcome the short-coming of average, and variance. So his statements that statisticians are not aware of some of the short-coming of average, and have no tools to deal with it is wrong.
1. He define a Random Variable (RV) as an uncertain Variable. Well, RV is mapping of representation of events and outcomes to numbers. For instance, a toss of a coin can have two outcome Head or Tail, so mathematically one can represent Head as , and tail by numbers x.
2. He also miss-informs the readers about the concept of dependency with his example of the two ladders that are connected. If ladder 1 has a probability of falling equal to 0.1, and ladder 2 has a probability of falling equal to 0.1, does it mean that the probability of them falling when connected is 0.01, of course not. By adding a connector we have changed the essence of the problem. This can be compared with throwing two dices. While the probability of having a 3 on each dice is 1/6, the probability that the sum (which is the result of throwing both dices at the same time) will be equal to 6 is not 1/36 but it is equal to the sum of the probabilities of throwing a 1 and 5, 2 and 4, 3 and 3, 5 and 1, 4 and 2 or 5/36 (not 1/36 as the author may want us to believe).
He changes the essence of the problem but mislead the readers that he is still using the same initial assumptions.
3. Lastly his description of the Black Swan is wrong. If a wheel has numbers between 0 and 1, and one is turning the wheel in hope that it will stop at a number larger than 0.2 that the wheel goes flying and breaks has no effect on the probability that it will stop at a certain number. The two events are independent, and we have a new problem that is created.
Now if the wheel has one number 0.000001 in it wheel, one may assume that the wheel will stop at this number is extremely slim, and will not even bother taking it into consideration, and it will be discredited. Hence, this number when it occurs it will be the same as the black swan.
4. He states that quant could not predict the outcome of the market meltdown, and that there exists no tool to predict such events. Well, there exists a distribution called (GEV) that does only that, while it is not publicized it does a good job.
This is not a statistics textbook! October 13, 2009
Lon Roberts - Author "SPC for Right-Brain Thinkers" (Plano, TX)
4 out of 4 found this review helpful
This book is difficult to pigeonhole, but I would describe it as an insightful, somewhat irreverent examination of risk and risk analysis from a "right-brain" perspective, rather than a statistics book for non-statisticians. (The irreverent part stems from the author's disregard for what he refers to as "Steam Era Statistics.") Rather than starting with statistical theory, equations, proofs, and Greek-alphabet soup, the author uses clever and engaging examples to clarify the principles.
If there is an "organizing principle" for the book, I believe the author sums it up in this statement: "My position is that decisions are made using the seat of the intellect at one extreme and the seat of the pants at the other and that the best decisions are those upon which both extremes agree."
Speaking from the standpoint of one who has a personal and professional interest in making abstruse mathematical and statistical concepts understandable to "right-brain thinkers," I am happy to report that this book lived up to my expectations.
Great book: not a how-to manual! October 12, 2009
FPC (USA)
2 out of 2 found this review helpful
This is a great awareness raising book, not a how-to manual. It is not a textbook either. The author clearly states this in the beginning. The book is very well written in prose vs. technical language, even though it deals with statistics. People who criticize it for being too long or having superfluous anecdotes are missing the point in my opinion. As an engineer and scientist, I have a good understanding of "steam era" statistics as well as other methods such as Monte Carlo simulations, etc., but I still found the book very interesting on many aspects, and it made its points in a manner that is extremely readable. Now that I am more aware, thanks to this book, of how I can better account for risk in many aspects of my work and investments, I can go and look for the resources to help and further educate myself.
Showing reviews 1-5 of 21
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