ab<strong>and</strong>oned in August 1936, but it is nevertheless remarkable that Khinchin had notcondemned any saboteur. Then, his comparison of pre-1917 with the 1930s is not convincingalso because, for example, British statisticians could have made similar conclusions in favorof the later period.Khinchin made mistakes when describing the history of probability which once againproves that in those times hardly anyone knew it. He favored the Laplacean justification ofthe method of least squares at the expense of Gauss; he did not mention Bienaymé; did notexplain Laplace’s part in proving the De Moivre – Laplace limit theorem, etc. But the mostdisappointing error (that bears on one of his important conclusions) is his failure to noticethat Chebyshev’s main papers in probability had appeared in French in Europe; again, hisOeuvres were published in Petersburg, in 1899 <strong>and</strong> 1907, in Russian <strong>and</strong> French. A similarstatement is true with regard to Markov <strong>and</strong> Liapunov. The second edition of Markov’streatise (1908) as well as three of his papers were translated into German in 1912. Liapunovpublished his memoirs in Petersburg, but in French, <strong>and</strong> both his preliminary notes appearedin the C.r. Acad. Sci. Paris. Moreover, Khinchin declares that Liapunov’s works inmechanics also remained unknown, but this is what Liapunov wrote to Markov on 24.3.1901(Archive, Russian Acad. Sci., Fond 173, Inventory 1, Item 11, p. 17), apparently inconnection with his forthcoming election to full membership at the Petersburg Academy ofSciences:You are asking me whether foreign scientists have referred to my works. If you needto know it, I ought to indicate […]He listed Poincaré, Picard, Appell, Tisser<strong>and</strong>, Levi-Cività <strong>and</strong> two lesser known figures<strong>and</strong> added that cannot say anything about Klein.Still, I hesitate to deny Khinchin’s overall conclusion that Western scientists had not beensufficiently acquainted with the work being done in Russia. An important related fact is that asimilar inference about Russian scholars would have been wrong. Here is Liapunov’sappropriate remark from his letter to Markov of 28.10.1895 (same Archive; Fond, Inventory<strong>and</strong> Item, p. 12):Believing that it is very desirable that Chebyshev’s contributions {Oeuvres} be published assoon as possible, I am prepared to participate here. […] I ought to say, however, that, owingto my rather superficial knowledge of French, I am afraid to take up translations fromRussian into French. As to the translations from French into Russian, I could undertake themalthough I do not quite sympathize with this business. […] I think that any {Russian}mathematician is able to read French.Days bygone![1] The theory of probability belongs to those very few branches of the mathematicalscience whose level of culture, even in pre-revolutionary Russia, was not lower than that inforeign countries. Even more can be stated: During the second half of the 19 th century <strong>and</strong> thefirst years of this {the 20 th } century, Russia was nearly the only country where themathematical foundations of probability had been cultivated as earnestly as it deserved owingto its outst<strong>and</strong>ing part in natural sciences, technology <strong>and</strong> social practice 1 . The Russiantheory of probability completely owes its exceptional st<strong>and</strong>ing to the works of Chebyshev.Being in this respect considerably ahead of his time, this great scholar paved new ways tosolving many problems dating back for a number of decades. Chebyshev also created inRussia the tradition, which, after being grasped by his followers, prompted many Russian
scientists to devote their energy, at the turn of the 19 th century, to the theory of probability;<strong>and</strong> which thus considerably fostered the development of this science.The status of probability in Europe had then been unenviable. Already in the 18 th century,the magnificent century of probability theory, Jakob Bernoulli <strong>and</strong> De Moivre discovered thetwo main laws of the doctrine of mass phenomena, the law of large numbers <strong>and</strong> the socalledlimit theorem, for the simplest particular case, – for the Bernoulli trials. The Bernoullitheorem stated that the relative frequency of any event in a given series of homogeneous <strong>and</strong>mutually independent trials should, with an overwhelming probability, be close to thatprobability which the event had at each trial. The De Moivre theorem (which had untilrecently been attributed to Laplace) stated that, under the same conditions, the probabilitiesof the values of this frequency can fairly be approximated by a formula now called thenormal distribution.Already Laplace repeatedly stated his belief in that both these theorems were valid undermuch more general conditions; in particular, he thought it highly probable that under mostgeneral conditions a sum of a very large number of independent r<strong>and</strong>om variables shouldpossess a distribution close to the normal law. He perceived here (<strong>and</strong> the furtherdevelopment of probability theory completely corroborated his viewpoint) the best way formathematically justifying the theory of errors of observations <strong>and</strong> measurements. Introducingthe hypotheses of elementary errors, that is, the assumption that the actual error is a sum of alarge number of mutually independent <strong>and</strong> very small as compared with this sum elementaryerrors, we may, on the strength of the abovementioned principle, easily explain the generallyknown fact that the distribution of the errors of observation is in most cases close to thenormal law. However, Laplace applied methods that did not allow to extend this principlebeyond the narrow confines indicated by the De Moivre theorem <strong>and</strong> were absolutelyinadequate for substantiating the theory of errors. Gauss is known to have chosen anotherway for attacking that goal, much less convincing in essence, but leading to it considerablyeasier 2 .In the interval between Laplace’s classical treatise <strong>and</strong> the appearance, in the second halfof the 19 th century, of the works of Chebyshev, only one bright flash, Poisson’s celebratedtreatise, had illuminated the sky of probability theory. Poisson generalized the Bernoullitheorem to events possessing differing probabilities in different trials; he called this theoremthelaw of large numbers having thus been the first who put this term into scientific circulation.There also, Poisson offered his illustrious approximation for the probabilities of seldomevents; <strong>and</strong>, finally, he made a new attempt at extending the De Moivre theorem beyond theboundaries of the Bernoulli trials. Like Laplace’s efforts, his attempt proved unsuccessful.And so, a twilight lasting all but a whole century fell over the European probability theory.Without exaggerating at all, it might be stated that, in those times, in spite of winning evermore regions of applied knowledge, European probability not only did not develop further asa mathematical science, – it literally degraded. The treatises written by Laplace <strong>and</strong> Poissonwere on a higher scientific level than the overwhelming majority of those appearing duringthe second half of the 19 th century. These latter reflect the period of decline when theencountered mathematical difficulties gradually compelled the minor scientists to follow theline of least resistance, to accept the theory of probability as a semi-empirical science only ina restricted measure dem<strong>and</strong>ing theoretical substantiation 3 . They usually inferred thereforethat its theorems might be proved not quire rigorously; or, to put it bluntly, that wrongconsiderations might be substituted for proofs. And, if no theoretical justification could befound for some principle, it was declared an empirically established fact. This demobilizationof theoretical thought, lasting even until now in some backward schools, has been to aconsiderable extent contributing to the compromising of the theory of probability as amathematical science. Even today, after the theory attained enormous successes during the
- Page 4 and 5: [3] I bear in mind the well-known p
- Page 6 and 7: successes of physical statistics. B
- Page 8 and 9: classes of independent facts whose
- Page 10 and 11: distribution is a corollary of the
- Page 12 and 13: examine in the first place the curv
- Page 14 and 15: 12. According to Bortkiewicz’ ter
- Page 16 and 17: generality, the similarities taking
- Page 18 and 19: one on another, as well as the corr
- Page 20 and 21: is inapplicable because the right s
- Page 22 and 23: Instead, Slutsky introduced new not
- Page 26 and 27: last decades, mathematicians more o
- Page 28 and 29: charged with making the leading ple
- Page 30 and 31: motion and a number of others) are
- Page 32 and 33: phenomena. It is self-evident that
- Page 34 and 35: Such new demands were formulated in
- Page 36 and 37: The addition of independent random
- Page 38 and 39: automatic lathes, etc. Here, the ma
- Page 40 and 41: 11. Kolmogorov, A.N. Grundbegriffe
- Page 42 and 43: period 1 and remained, until the ap
- Page 44 and 45: of the analytical tool rather than
- Page 46 and 47: with probability approaching unity,
- Page 48 and 49: logic. The ensuing vagueness in his
- Page 50 and 51: 2. Gnedenko, B.V. (1949), On Lobach
- Page 52 and 53: will be sufficient, although not ne
- Page 54 and 55: nlimk = 1P(| k (n) - m k (n) | > H
- Page 56 and 57: favorite classical issue as the gam
- Page 58 and 59: and some quite definite (not depend
- Page 60 and 61: influenced by a construction that a
- Page 62 and 63: P ij (1) = p ij (1) , P ij (t) =kP
- Page 64 and 65: 4.2d. Bebutov [1; 2] as well as Kry
- Page 66 and 67: are yet no limit theorems correspon
- Page 68 and 69: described, from the viewpoint that
- Page 70 and 71: conditional variance and determined
- Page 72 and 73: Romanovsky [45] and Kolmogorov [46]
- Page 74 and 75:
Let S be the general population wit
- Page 76 and 77:
Part 1. Russian/Soviet AuthorsAmbar
- Page 78 and 79:
2. On necessary and sufficient cond
- Page 80 and 81:
Gnedenko, B.V., Groshev, A.V. 1. On
- Page 82 and 83:
52. ( (Mathematical Principl
- Page 84 and 85:
Kozuliaev, P.A. 1. Sur la répartit
- Page 86 and 87:
Obukhov, A.M. 1. Normal correlation
- Page 88 and 89:
30. Généralisations d’un théor
- Page 90 and 91:
22. Alcune applicazioni dei coeffic
- Page 92 and 93:
10. A.N. Kolmogorov. The Theory of
- Page 94 and 95:
Kuznetsov, Stratonovich & Tikhonov
- Page 96 and 97:
In the homogeneous case H s t = H t
- Page 98 and 99:
to such a generalization. He only s
- Page 100 and 101:
In the particular case of a charact
- Page 102 and 103:
as it is usual for the modern theor
- Page 104 and 105:
1. {The second reference to Pugache
- Page 106 and 107:
Smirnov, Romanovsky and others made
- Page 108 and 109:
determined the precise asymptotic c
- Page 110 and 111:
for finite values of N, M and R 2 .
- Page 112 and 113:
Mikhalevich’s findings by far exc
- Page 114 and 115:
Uch. Zap. = Uchenye ZapiskiUkr = Uk
- Page 116 and 117:
Khinchin, A.Ya. 43. Math. Ann. 101,
- Page 118 and 119:
7. DAN 115, 1957, 49 - 52.Pinsker,
- Page 120 and 121:
Anderson, T.W., Darling, D.A. (1952
- Page 122 and 123:
Statistical problems in radio engin
- Page 124 and 125:
observations for its power with reg
- Page 126 and 127:
securing against mistakes (A.N. Kry
- Page 128 and 129:
of the others, then its distributio
- Page 130 and 131:
In Kiev, in the 1930s, N.M. Krylov