The History of Statistics: The Measurement of Uncertainty before 1900

by Stigler

This magnificent book is the first comprehensive history of statistics from its beginnings around 1700 to its emergence as a distinct and mature discipline around 1900. Stephen M. Stigler shows how statistics arose from the interplay of mathematical concepts and the needs of several applied sciences including astronomy, geodesy, experimental psychology, genetics, and sociology. He addresses many intriguing How did scientists learn to combine measurements made under different conditions? And how were they led to use probability theory to measure the accuracy of the result? Why were statistical methods used successfully in astronomy long before they began to play a significant role in the social sciences? How could the introduction of least squares predate the discovery of regression by more than eighty years? On what grounds can the major works of men such as Bernoulli, De Moivre, Bayes, Quetelet, and Lexis be considered partial failures, while those of Laplace, Galton, Edgeworth, Pearson, and Yule are counted as successes? How did Galton’s probability machine (the quincunx) provide him with the key to the major advance of the last half of the nineteenth century?

Stigler’s emphasis is upon how, when, and where the methods of probability theory were developed for measuring uncertainty in experimental and observational science, for reducing uncertainty, and as a conceptual framework for quantitative studies in the social sciences. He describes with care the scientific context in which the different methods evolved and identifies the problems (conceptual or mathematical) that retarded the growth of mathematical statistics and the conceptual developments that permitted major breakthroughs.

Statisticians, historians of science, and social and behavioral scientists will gain from this book a deeper understanding of the use of statistical methods and a better grasp of the promise and limitations of such techniques. The product of ten years of research, The History of Statistics will appeal to all who are interested in the humanistic study of science.

Genres: History, Mathematics, Science, Nonfiction, History Of Science, Sociology, Economics

428 pages, Paperback

First published September 26, 1986

Reviews

[Guillaume Belanger · Rating 4 out of 5]

In two words: very good. This is a remarkable piece of work. I have rarely read books such as this in which the amount of information that has been read, processed, analysed and then synthesised by the author is so massive and spanning several centuries. This is really very impressive to someone like me who appreciates first hand the difficulties involved, the motivation needed, and the shear amount of energy that must be invested in reading large amounts of highly technical, and, as applicable to this case, very old in style of presentation and notation, in order to first understand and then extract its essence as well as its relevance to the evolution of a field as a whole.

It has taken me more than two years to finish because it is very long, because my (but I could write in general 'our') interest in a particular subject naturally waxes and wanes depending on we are doing and concerned with from day to day and month to month, because some sections are very technical, and because some of them were more interesting to me than others. In addition, although the text is very well written and I have not picked up any misprints (which is amazing compared to most books I have read), the typesetting and layout is not conducive to reading for long periods of time: the font is too small, the layout is too tight, there are not enough chapters, sections nor subsections.

Lastly, I found that it ended very abruptly, as if the author "needed" to finish the book and just ended it without taking the time to write a fuller conclusion that would have allowed the reader to get a global summary of the contents of the book in somewhat greater detail than what was done in a few pages of text. But then again, maybe this was intended by the author. I just know that I would have greatly appreciated a detailed conclusion reviewing the book in 10 to 20 pages, say, in order to clearly tie in all the elements of the book.

Even in the light of these minor reservations, I whole heartedly encourage anyone interested in statistics to read this book. It is very well worth the investment, and I found it, indeed, very inspiring.

[Lee Richardson · Rating 5 out of 5]

An absolutely incredible book. Have written summaries of each chapter on laptop, will translate and fill in later.

[John Isles · Rating 3 out of 5]

Rather more detail than I needed, and I wish the book had gone on to discuss 20th-century changes in statistical thinking.

[Alecsphys · Rating 4 out of 5]

This book apart containing a paramount quantity of information, provide you a clear picture of how much difficult can be, also in science, to fruitful transfer ideas from one field to another one. It takes time and it requires brave people able to dismount a priori believes. Something that today seems obvious to us, like doing a regression of several collected data, it was absolutely not so evident in the past. Many centuries were needed before what we call statistics was born. The author of the book, Stigler, did an excellent job in recollecting all such historical information, that provided to me the root rationale of why some topics where so underlined during my university studies. A example for that is the beauty behind the Galton's Quincunx.

[Dan · Rating 4 out of 5]

The book covers two themes; combination of observations (in astronomy and geodesy), and use of probability models for inferential purposes.
"Modern statistics provides a quantitative technology for empirical science; it is a logic and methodology for the measurement of uncertainty and for an examination of the consequences of that uncertainty in the planning and interpretation of experimentation and observation."
"The history of statistics can encompass the history of all of science."
- Stephen Stigler

[Zina · Rating 5 out of 5]

This book helps understand how statistics came about the way it is. It paints great portraits of the various [mostly, quirky] characters who contributed to it and is a lot of fun. Anybody who loves quantitative things will find this book a delight. Anybody who hates quantitative things might get to be a bit more tolerant after getting to see the faces behind it.

[Timothy · Rating 1 out of 5]

Didn’t finish. Too technical.

[Farouk Ramzan · Rating 4 out of 5]

Wow! It was boring but not as much as Dante's The Divine Comedy.

[Gennady Gorin · Rating 4 out of 5]

Took two and a half years to get through the first half and three hours to do the second half. It's good though feels a little dated.

[Farouk Ramzan]

Wow! It was boring but not as much as Dante's The Divine Comedy.

[Adam]

Got through the first 50 pages of this, realizing I wasn't on the same page with his terminology but feeling like I was getting something out of it. Then it dawned on me that while I for some reason assumed he was talking about the derivation of multiple linear regression, he was really just talking about single regression, and that the disparity was only going to get worse, I decided to quit. I feel like I understand a decent amount of statistics but Stigler seems to be writing this for capital-M Mathematicians who apparently use a peculiar set of jargon that isn't even the same as the practical stats material I was taught.

[Jason · Rating 4 out of 5]

This is a comprehensive book detailing the history of statistics. The characters and their breakthrough are described in an entertaining but informative manner. I highly recommended this book for social scientists and researchers, but it may be too boring for a lay person.

[Isaac Galatzer-levy · Rating 5 out of 5]

Really interesting history: accessible if you have some statistics background.

[Alan · Rating 3 out of 5]

It took a lot of effort to get through, even being fascinated by many of the topics

[Vishal]

cool

[Matthew Giobbi · Rating 5 out of 5]

Thorough. Internalist, not critical history.