The Seven Pillars of Statistical Wisdom

Every student of an abstract subject like maths, physics or even philosophy is familiar with this: you are introduced to a foundational concept yet it seems pretty counterintuitive, and you can think of a number of reasons why the said concept ought to be considered problematic. Yet somehow, the textbooks are less than sympathetic.My advice is to check the history of the under-motivated concept. The original formulations were often so much more compelling, especially when you realise precisely what problem their authors were trying to solve. Your own misgivings may well be represented in critiques by the innovator’s contemporaries.It was the very success of later generations which led to the wholesale reconceptualisation of their subject’s foundations.And so it is with statistics, a subject where deep ideas are often obscured by a focus on technique, and where it sometimes seems that little distinguishes a correct line of argument from an equally plausible, but fallacious, alternative.Professor Stephen Stigler, in this determinedly historical book, starts with a concept as apparently trivial as the mean, or average, of a sequence of observations. Even this is counterintuitive as it requires discarding information, the individuality of the observations. By what right are ‘bad’ measurements to be treated in the same way as ones we think, or know, to be of higher quality? It took quite a few years for the idea to catch on.Stigler’s second pillar, information measurement, looks at the processing of large data sets. Opinion polls have made us somewhat aware that the accuracy of the proposed mean is proportional to the square root of the number of observations, not the absolute number.Sampling was applied to the Royal Mint in Isaac Newton’s time, to ensure that the coins they produced used the right amount of gold. In the absence of a correct theory of standard deviation, the tolerance boundaries were set way too wide. Stigler dryly notes that Newton was warden, then master of the Royal Mint from 1696 to 1727 and that on his death in that year left a sizeable fortune. “But evidently his wealth can be attributed to investments, and there is no reason to cast suspicion that he had seen the flaw in the Mint’s procedures and exploited it for personal gain.”Later chapters deal with hypothesis testing (pillar 3); statistical processing within the dataset itself, without reference to population norms – as in Student’s t-test (pillar 4); regression to the mean - a concept which proved very hard to pin down (pillar 5); experimental design, particularly when varying multiple qualities at the same time (pillar 6); and finally pillar 7, the notion that a complicated phenomenon may be simplified by subtracting the effect of known causes, leaving a residual phenomenon to which attention may now be focused.If you are both interested and well-versed in statistics, you will find this book illuminating and witty. The converse also applies.

In interesting read and a useful insight into the historical and structural core of statistics. Many people will have studied stats to pass exams and will understand the concepts from this perspective. This book goes beyond this level to provide a deeper understanding of where and when the ideas emerged. Not a 'necessary' read but one that cements stats in your memory in a way that no other book that I've read has.

The Seven Pillars of Statistical Wisdom provides an historical account of how the identified pillars were invented and developed. It is fascinating, but I feel the focus on the history detracts somewhat from the actual technicalities. Indeed, in several cases the author seems to assume prior knowledge of the very statistical concepts being introduced.The book is richly illustrated with figures and tables from the original publications, some dating back hundreds of years. It is good to see this original material, but it would be nice also to see a modern rendering of the key figures, as the originals can sometimes be over-embellished and obscure.This is worth reading for the historical insights. I learned lots of delicious little snippets, such as the fact that for many years after its publication, no one used Student’s t-test, not even Student (William Sealy Gosset) himself! However, I didn’t learn as much statistics as I had hoped.

Good read..

My fiancé wanted this and seems happy with it.

Thought it would be more insightful. Fairly ordinary book

Statistic history, not really about statistic methods per say.

Great read on how we got where we are and what to look forward to.

For core technical persons only!

Um pouco técnico demais para iniciantes, mas um bom livro. Poderia ter mais fatos históricos. O inglês é fácil de entender para estrangeiros.

This book explains seven statistical principles. It language is simple and very easy to understand. If you are studying statistics, the book would be very helpful.

This book was recommended by a biostatistics professor with a growing interest in the history of statistics, and it definitely is meeting expectations.

I thought that this book was directed to someone who had a somewhat broader and deeper grasp of statistics than I have. My background in statistics is fair, but certainly not at a PhD level. I found the categorization into seven "pillars of wisdom" to be a useful perspective. I also thought that the historical incidents discussed in the book were very interesting, and in some cases eye-opening for me. I especially appreciated the discussion of twentieth century statistics, but this does not proceed very far into that fruitful century. The book has very much fired my love of the field, and induced me to read some of the old books that are mentioned in the book. I can strongly recommend this book if you have a background in statistics to draw on.

This a great interesting book, that helped me understanding concepts that I always used and taken them for given, but always puzzled me. The author guides the reader to the development of these concepts through an historical perspective, merging philosophical with science. Some parts of the book are very clear and well written, but I found other parts more nebulous and not as well written, requiring deeper familiarity of the concept itself to be understood. Nevertheless, I really enjoyed reading this unique book.

Interesting historical reading giving some explanation of how statistics today was derived. However, a bit dry at some places and, if the reader doesn't put some thought into the explanations of origins, seemingly pointless to the non-statistically oriented. In other words, not a needed reference but (after working with statistics for a while) some explanation of how and why statistics got its recognition of being important.

Fascinating read if you are into statistics. As other reviewers have noted, much of this book won't make sense to someone with no background in statistics. However for those who do have such a background, it is fascinating. I learned a lot about some ideas I am familiar with but hadn't thought of in this way or hadn't placed into their historical context. I bought the book for my graduate statistics professor --- my hunch is he will get even more out of it than I did.

If you're interested in the history and philosophy behind statistics, not just the equations, this book is recommended. Sometimes things like this can help you see and internalize the 'big picture' in the way random collections of blog posts or papers can't.

As someone working in the field of data analytics, I found the Seven Pillars of Statistical Wisdom to be an exceptional guide to the history of the basic concepts of statistics. A few caveats, however. The book assumes a basic knowledge of these concepts, so non-scientists may be better off choosing a different book if they simply want a introduction to statistics. Second, the balance between the history of these ideas and explanation of them sometimes leans in the historical direction (in my personal opinion too much) so only scientists who like learning about the history of the analytic tools they use will find the book engaging. All that said, Professor Stigler is not only a accomplished statistician but a good writer who can make a discussion of routine statistical concepts interesting to someone whose work involves these every day. Highly recommended but to a select circle of readers.

I'm not sure that the author was clear on his intended audience. At some points he explains relatively simple concepts but at other points (and they were the majority) he seems to assume fairly advanced statistical knowledge of the reader. I consider myself to have above average statistical education but I finally gave up around page 80. It is a shame as there was a lot of interesting background on the development of statistics but this is not a book for even the relatively well informed reader, despite how it is presented in the advertising.

This is a half-baked, tedious essay with a grandiose title, that is extremely hard to read (I made through all of it). Most of the historical examples selected to illustrate the "seven wisdoms" are borderline relevant trivia, intended to show the author's erudition, and are not in the least illuminating. Mainstream developments in statistics, such as Bayesian methods, are barely mentioned. The author implicitly assumes that the reader is a historian of statistics interested in such historical curiosities, rather than someone looking for a broader perspective of statistics.