British Medical Journal
: Review of
the 1st edition of
Box (p. 482) lists 5 reviews, signed ones by “Student” (W. S. Gosset), Leon Isserlis, Egon Pearson and unsigned ones, in the British Medical Journal and Nature. She missed the very enthusiastic review from the American statistician Harold Hotelling.
All the reviews are available on the web, the one reproduced here and
They are all worth reading for each gives a different perspective on the book.
The BMJ review
Apart from Hotelling, all the reviewers had reservations about the book—it was too difficult and contained no proofs—but, as Frank Yates (1990, p. xii) says, only the BMJ review was “really hostile.” Yates quotes from the second paragraph of the review
The trained statistician interested in Mr. Fisher’s researches will miss a detailed justification of his conclusions … Even if the statement that Professor Pearson’s treatment of a fundamental problem contained a “serious error” had not been disputable, and therefore improper in a work addressed to elementary students, it would have reminded anyone of Macaulay’s remark on a similar situations—“just so we have heard a baby, mounted on the shoulders of its father, cry out, “how much taller I am than Papa!”
The reviewer was responding to Fisher’s statement that Karl Pearson’s paper of 1900 “contained a serious error, which vitiated most of the tests of goodness of fit made by this method” [I §4 p. 17] and to Fisher’s way of presenting his version of how the tests should be done. Yates remarks of Fisher’s presentation, “Actually the point was discussed by Fisher (Example 8) [IV. §20 p. 81], which for clarity of statement and convincingness of argument would be difficult to better.” Yates came on the scene when Fisher’s arguments had had time to sink in and I think he underestimated the difficulty for the first readers. It was not family partiality that led Karl’s son, Egon Pearson, to write in his review, “it is necessary to read the book in conjunction with the author's papers published elsewhere, and one must confess to some difficulty in following several of the proofs based on the idea of degrees of freedom.”
The review was unsigned. The quotation from Macaulay may be a clue
to the author for this tart variation on the “shoulders of giants” theme was no
commonplace and another put-down from the same source appeared in the
statistical literature the following year.
The reviewer’s assessment was pure Greenwood. In 1933 Fisher succeeded Pearson in the Galton chair. Greenwood wrote Fisher a friendly letter of congratulations yet still reminded him of his dependence on Pearson. (Letter of 10 June 1933 reproduced in Bennett (1990: 318)
There is, in my opinion, no other man alive worthy to sit in old K. P.’s chair; his mantle has descended on our shoulders and a double portion of his spirit is yours. Like all of us, you owe him much. If K. P. had never lived, you would have assuredly been one of our foremost men of science but very likely your field of work would not have been statistics, but, perhaps, pure mathematics. You will repay the debt not by silly adulation of the “illustrious predecessor”—as so often happens when a great personality leaves the stage—but by carrying the work further. This appointment really makes me happy for—although K. P. has often enough wounded my feelings and insulted my friends–I still love the man and venerate his genius, I should have been sad if his kingdom had fallen into the hands of a second rater.
Greenwood recalled how much Pearson meant to him—mistakes and all—in the opening paragraphs of his Presidential Address to the Statistical Society given a few months after Pearson’s death.
Yates’s foreword to Statistical Methods, Experimental Design and Scientific Inference,
B. Macaulay’s review of Mackintosh’s History
of the Revolution in
a perspective on Fisher’s book see A. W. F. Edwards, (2005) “
Anon. (1926) Review of Statistical Methods for Research Workers (R. A. Fisher), British Medical Journal, 1, 578-9.
Mr. Fisher has designed his book for readers without special mathematical training, and is conscious that the inclusion of a good deal of matter which is “advanced,” and has, indeed, not been published before, needs some explanation. If he feared that he was likely to fall between two stools—to produce a book neither full enough to satisfy those interested in statistical algebra nor sufficiently simple to please those who dislike algebra—we think that Mr. Fisher’s fears are justified by the result. The laboratory worker will, as we have said, find the book useful when dealing with small samples, but will not find in it a sufficiently simple and comprehensive account of the general principles of statistical methodology. The illustrations are sometimes—for example, that dealt with on pages 94 et seq. [IV. §22]—only illuminating to students with special knowledge of modern genetics. The trained statistician interested in Mr. Fisher’s researches will miss a detailed justification of his conclusions, and may resent the somewhat arrogant way in which the law is laid down upon points respecting which there is difference of opinion among persons possibly as well informed as Mr. Fisher. A conspicuous example of this latter failing is the reference to Professor Karl Pearson on page 17 [I. §4]. Even if the statement that Professor Pearson’s treatment of a fundamental problem contained a “serious error” had not been disputable, and therefore improper in a work addressed to elementary students, it would have reminded anyone of Macaulay’s remark on a similar situations—“just so we have heard a baby, mounted on the shoulders of its father, cry out, “how much taller I am than Papa!”