U 4 ]N[ + 3U 22 ]N[ = [(N – 1)/N] (µ 4 + 3µ 2 2 )or, when passing on to a uniform system, ofU 4 [N] + 3U 22 [N] = [(N – 1)/N] (M 4 + 3M 22 ).Supposing that N = S, we indeed find that(µ 4 + 3µ 2 2 ) = U 4 [S/S] + 3U 22 [S/S] = [(S – 1)/S] (M 4 + 3M 22 ),S [–2] (M 4 + 3M 22 ) = S 2 (µ 4 + 3µ 2 2 ).12. The pattern of an unreturned ticket is contrary to that of an attached ticket just as, inthe Lexian terminology, a scheme of a supernormally stable statistical series is opposed tothe arrangement of a series with a subnormal stability.13. The uniformity of the system of trials obtained on the basis of the new layout is verysimply revealed by means of a test established in the next section.14. Magnitudes x (i1) , x (i2) , …, x (iN) represent some of the values x (1) , x (2) , …, x (k) ; some or allof them may be identical. It is assumed here as it was before that the law of distribution ofthe variable remains fixed.References1. Bortkiewicz, L., von (1917), Die Iterationen. Berlin.2. Chuprov, A.A. (1918 – 1919), Zur Theorie der Stabilität statistischer Reihen. Sk<strong>and</strong>.Aktuarietidskr., t. 1, pp. 199 – 256; t. 2, pp. 80 – 133.3. --- (1918 – 1919 <strong>and</strong> 1921), On the mathematical expectation of the moments offrequency distributions. Biometrika, vol. 12, pp. 140 – 169 <strong>and</strong> 185 – 210; vol. 13, pp. 283 –295.4. --- (1922), Ist die normale Dispersion empirisch nachweisbar? Nordisk Stat. Tidskr., t. 1,pp. 369 – 393.5. --- (1923), On the mathematical expectation of the moments of frequency distributionsin the case of correlated observations. Metron, t. 2, pp. 461 – 493 <strong>and</strong> 646 – 683.6. Seneta, E. (1987), Chuprov on finite exchangeability, expectation of ratios <strong>and</strong> measuresof association. Hist. Math., vol. 14, pp. 243 – 257.7. <strong>Sheynin</strong>, O. (1990, in Russian), Chuprov. Göttingen, 1996.12. A.N. Kolmogorov. Determining the Center of Scattering<strong>and</strong> the Measure of Precision Given a Restricted Number of ObservationsIzvestia Akademii Nauk SSSR, ser. Math., vol. 6, 1942, pp. 3 – 32Foreword by TranslatorThis paper was apparently written hastily, <strong>and</strong>, at the time, its subject-matter did notperhaps belong to the author’s main scientific field. He mixed up Bayesian ideas <strong>and</strong> theconcept of confidence intervals <strong>and</strong> in §4 he showed that the posterior distribution of aparameter was asymptotically normal without mentioning that this was due to the wellknownBernstein- von Mises theorem. Points of more general interest are Kolmogorov’sdebate with Bernstein on confidence probability <strong>and</strong>, in Note 11, a new axiom of the theory ofprobability. The author apparently set high store by artillery (even apart from ballistics) as afield of application for probability theory. Indeed, this is seen from Gnedenko’s relevantstatement [1, p. 211] which he inserted even without substantiating it, a fact about which I
then expressed my doubts). And Gnedenko certainly attempted to remain in line with hisformer teacher.In both of Kolmogorov’s papers here translated, apparently for the benefit of his readers,the author numbered almost all the displayed formulas whether mentioned in the sequel ornot. I only preserved these numbers in the paper just below.1. Gnedenko, B.V., <strong>Sheynin</strong>, O.B. (1978, in Russian), Theory of probability. A chapter inMathematics of the 19 th Century (pp. 211 – 288). Editors, A.N. Kolmogorov, A.P.Youshkevich. Basel, 1992 <strong>and</strong> 2001.* * *This paper is appearing owing to two circumstances. First, intending to explicate hisviewpoint <strong>and</strong> investigations on the stochastic justification of mathematical statistics inseveral later articles, the author considers it expedient to premise them by a detailed criticalexamination of the existing methods carrying it out by issuing from a sufficiently simpleclassical problem of mathematical statistics. For this goal it is quite natural to choose theproblem of estimating the parameters of the Gaussian law of distribution given n independentobservations.Second, the author was asked to offer his conclusion about the differences of opinionexisting among artillery men on the methods of estimating the measure of precision byexperimental data, see for example [10 – 12]. The author became therefore aware of thedesirability of acquainting them with the results achieved by Student <strong>and</strong> Fisher concerningsmall samples. Exactly these issues definitively determined the concrete subject-matter ofthis article.It is clear now that the article only mainly claims to be methodologically interesting. Theauthor believes that the new factual information is represented here by the definition ofsufficient statistics <strong>and</strong> sufficient systems of statistics (§2) <strong>and</strong> by the specification of theremainder terms in limit theorems (§4). The need to compare critically the variousapproaches to the studied problems inevitably led to a rather lengthy article as compared withthe elementary nature of the problems here considered.Introduction. Suppose that r<strong>and</strong>om variablesx 1 , x 2 , …, x n (1)are independent <strong>and</strong> obey the Gaussian law of distribution with a common center ofscattering a <strong>and</strong> common measure of precision h. In this case the n-dimensional law ofdistribution of the x i ’s is known to be determined by the densityf(x 1 ; x 2 ; …; x n |a; h) = (h n / n/2 )exp (– h 2 S 2 ), (2)S 2 = (x 1 – a) 2 + (x 2 – a) 2 + … + (x n – a) 2 . (3)Instead of formula (2) it is sometimes convenient to apply an equivalent formulaf(x 1 ; x 2 ; …; x n | a; h) = (h n / n/2 )exp[– h 2 S 1 2 – nh 2 ( x – a) 2 ], (4)x = (x 1 + x 2 +… + x n )/n, S = (x 1 – x ) 2 + (x 2 – x ) 2 + … + (x n – x ) 2 . (5; 6)All courses in probability theory for artillery men consider the following three problems.1. Assuming h to be known, approximately estimate a by the observed values of (1).2. Assuming that a is known, approximately estimate h by the same values.3. Again issuing from (1), approximately determine both a <strong>and</strong> h.
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of All Countries and to the Entire
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(Coll. Works), vol. 4. N.p., 1964,
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individuals of the third class, the
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From the theoretical point of view
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Second case: Each crossing can repr
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On the other hand, for four classes
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f i = i S + i , i = 1, 2, 3, 4, (
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f 1 = C 1 P(f 1 ; …; f n+1 ), C 1
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ut in this case f = 2 , f 1 = 2 ,
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I also note the essential differenc
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A 1 23n1 + 1 A 1 A 1 … A 11A 2 A
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coefficient of 2 in the right side
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h(A r h - c h A r 0 ) = - A r0we tr
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Notes1. Our formulas obviously pres
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Bernstein’s standpoint regarding
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Corollary 1.8. A true proposition c
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It is important to indicate that al
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ut for the simultaneous realization
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devoid of quadratic divisors and re
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propositions (B i and C j ) can be
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A ~ A 1 and B = B 1 , we will have
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included in a given totality as equ
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For unconnected totalities we would
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proposition given that a second one
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On the other hand, let x be a parti
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totality is perfect, but that the j
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In this case, all the finite or inf
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probabilities p 1 , p 2 , … respe
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where x is determined by the inequa
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totality of the second type (§3.1.
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x = /2 + /(23) + … + /(23… p n
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that the fall of a given die on any
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infinitely many digits only dependi
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10. (§2.1.5). Such two proposition
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F(x + h) - F(x) = Mh, therefore F(x
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“confidence” probability is bas
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x1+ Lp n (x) x1− Lx1+ Lf(t)dt < x
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|(x 1 ; t 0 ; t 1 ) - 1 t0tf(t)dt|
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5. The distribution ofξ , the arit
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P(x 1i < x) = F(x; a i ) = C(a i )
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egards his promises. Markov shows t
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other solely and equally possible i
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notion of probability and of its re
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However, already in the beginning o
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the revolution. My main findings we
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Nevertheless, Slutsky is not suffic
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path that would completely answer h
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on political economy as well as wit
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scientific merit. Borel was indeed
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[3] Already in Kiev Slutsky had bee
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different foundation. The difficult
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5. On the criterion of goodness of
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