The History of Statistics

The Measurement of Uncertainty before 1900

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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 mathema

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 questions: 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 quantative 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.

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Ha scritto il 13/07/07
Stigler, Stephen M. (1986). The History of Statistics. The Measurement of Uncertainty before 1900. Cambridge: Belknap Harvard. 2003.

Il programma del libro, dichiarato nell’introduzione, è molto chiaro:

Statistics, as we now understand th

Il programma del libro, dichiarato nell’introduzione, è molto chiaro:

Statistics, as we now understand the term, has come to be recognized as a separate field only in the twentieth century. But this book is a history of statistics before 1900. Thus my subject is not the entire development of a single discipline but rather the story of how that discipline was formed, of how a logic common to all empirical science emerged from the interplay of mathematical concepts and the needs of several applied sciences (p. 1).

Non che Stigler non mantenga la promessa. Ma la mantiene con un’attenzione ossessiva agli aspetti formali, alle dimostrazioni matematiche. Chiaramente innamorato della sua materia, abbandona spesso la storia delle idee – l’aspetto per me più interessante – per soffermarsi sui passaggi e le dimostrazioni matematiche, talora presentate due volte (una con il formalismo dell’epoca e una in versione moderna).

Perciò, mi sento di raccomandarlo agli addetti ai lavori, e non ai semplici curiosi. Un trattato tecnico, non un’opera di divulgazione: detto da me, è una critica severa.

Non di meno, il libro contiene alcune perle. Questa, per me, è la migliore:

Observations and statistics agree in being quantities grouped about a Mean; they differ, in that the Mean of observations is real, of statistics is fictitious. The mean of observations is a cause, as it were the source from which diverging errors emanate. The mean of statistics is a description, a representative quantity put for a whole group, the best representative of the group, that quantity which, if we must in practice put one quantity for many, minimizes the error unavoidably attending such practice. Thus measurement by the reduction of which we ascertain a real time, number, distance are observations. Returns of prices, exports and imports, legitimate and illegitimate marriages or births and so forth, the averages of which constitute the premisese of practical reasoning, are statistics. In short observations are different copies of one original; statistics are different originals affording one “generic portrait”. Different measurements of the same man are observations; but measurements of different men, grouped around l’homme moyen, are prima facie at least statistics [Edgeworth, Francis Ysidro. 1885. “Observations and statistics: an essay on the theory of errors and the first principles of statistics”. Transactions of the Cambridge Philosophical Society 14: 138-169] (p. 309) ...Continua


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