ξ 1 , ξ 2 , ..., ξ n , ... (4.4)tak<strong>in</strong>g <strong>the</strong> same values0, ± 1, ± 2, ..., ± mwith <strong>the</strong> same probabilitiesP{ξ i = m} = p m .Such variables are called identically distributed. Probabilities p m arearbitrary, <strong>the</strong>y only obey <strong>the</strong> condition <strong>of</strong> add<strong>in</strong>g up to 1 <strong>and</strong>sufficiently rapidly decrease as m → ± ∞. More precisely, it isnecessary that <strong>the</strong> variables ξ i have a f<strong>in</strong>ite expectation <strong>and</strong> a f<strong>in</strong>itevariance∞∞2 2Eξi= ∑ mpm = a, varξi= ∑ ( m − a) pm= σ .m=−∞m=−∞O<strong>the</strong>rwise, <strong>the</strong> set <strong>of</strong> probabilities {p m } is absolutely arbitrary. It can<strong>the</strong>refore be impossible to describe that set by any f<strong>in</strong>ite number <strong>of</strong>parameters.Laplace discovered that for a large number <strong>of</strong> terms <strong>of</strong> <strong>the</strong> set (4.4)<strong>the</strong> distribution <strong>of</strong> <strong>the</strong>ir sum becomes <strong>in</strong>comparably simpler than that<strong>of</strong> <strong>the</strong>ir separate terms so that, allow<strong>in</strong>g for some additional conditions(Gnedenko 1950, Chapter 8) 6 ,21 −xn( n)σ nP{ξ 1+ ... + ξn= m} ≈ exp[ − ],2π 2m − naxn( m) = . (4.5a,b)σ nIt is beneficial to bear <strong>in</strong> m<strong>in</strong>d <strong>the</strong> follow<strong>in</strong>g simple considerationswhich help to underst<strong>and</strong> <strong>the</strong> geometric mean<strong>in</strong>g <strong>of</strong> equality (4.5).Suppose that we desire to show graphically <strong>the</strong> distribution <strong>of</strong> eachr<strong>and</strong>om variable (4.4) <strong>and</strong> <strong>the</strong>ir sum. We choose an abscissa axis,<strong>in</strong>dicate po<strong>in</strong>ts0, ± 1, ± 2, ..., ± m ...<strong>and</strong> show probability as a rectangle with base 1, its midpo<strong>in</strong>t be<strong>in</strong>g atm, <strong>and</strong> area (that is, its height) p m . We will have some, generallyspeak<strong>in</strong>g, irregular set <strong>of</strong> rectangles. An attempt to show <strong>the</strong>distribution <strong>of</strong> <strong>the</strong> probabilities <strong>of</strong> <strong>the</strong> sum <strong>of</strong> those variables for alarge n will be unsuccessful because <strong>the</strong> possible values <strong>of</strong> that sumcan be very large <strong>and</strong> <strong>the</strong> probabilities <strong>of</strong> <strong>the</strong> separate values, small, ascan be proven. A change <strong>of</strong> <strong>the</strong> scale will be <strong>the</strong>refore needed so thatshow<strong>in</strong>g <strong>the</strong> values <strong>of</strong> <strong>the</strong> r<strong>and</strong>om variable32
(1/B n )(m − A n )<strong>in</strong>stead <strong>of</strong> <strong>the</strong> value <strong>of</strong> <strong>the</strong> sum m = (ξ 1 + ...+ ξ n ) will be necessary.And now <strong>the</strong> essence <strong>of</strong> Laplace’s discovery can be expressed by as<strong>in</strong>gle phrase: <strong>the</strong> figure should be shifted byA n = E(ξ 1 + ... + ξ n ) = na<strong>and</strong> <strong>the</strong> coefficient <strong>of</strong> <strong>the</strong> change <strong>of</strong> <strong>the</strong> scale should be equal toBn= var(ξ + ... + ξ ) = σ n.1nThe r<strong>and</strong>om variable* 1sn= [(ξ1+ ... + ξn) − E(ξ1+ ... + ξn)]var(ξ + ... + ξ )1n(4.6)is called <strong>the</strong> normed sum. Obviously,* *Esn= 0, var sn= 1<strong>and</strong> <strong>the</strong> numbers (4.5b) are <strong>the</strong> possible values <strong>of</strong> that normed sum. Letus attempt to show its probabilities as rectangles with bases1xn( m + 1) − xn( m) = ,σ n<strong>the</strong>ir midpo<strong>in</strong>ts co<strong>in</strong>cid<strong>in</strong>g with po<strong>in</strong>ts x n (m) <strong>and</strong> areas equal toprobabilitiesP s x m P m*{n=n( )} = {ξ1+ ... + ξn= }.The heights <strong>of</strong> <strong>the</strong>se rectangles should be*σ nP{ sn = xn ( m)} = σ nP{ξ 1+ ... + ξn= m}.Thus, because <strong>of</strong> (4.5a) <strong>the</strong> upper bases <strong>of</strong> <strong>the</strong>se rectangles will bealmost exactly situated along a curve described by equation21 xy = y( x) = exp[ − ](4.7)2π 2<strong>in</strong>dependent <strong>of</strong> anyth<strong>in</strong>g <strong>and</strong> calculated once <strong>and</strong> for all.A result absolutely not foreseen <strong>and</strong> almost miraculous! Disorder <strong>in</strong>probabilities p m somehow gives birth to a unique curve (4.7) whichsimply occurs by summ<strong>in</strong>g r<strong>and</strong>om variables <strong>and</strong> transform<strong>in</strong>g <strong>the</strong>scale <strong>of</strong> <strong>the</strong> figure. That is Laplace’s remarkable discovery without33
- Page 1 and 2: Studies in the History of Statistic
- Page 3 and 4: Introduction by CompilerI am presen
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- Page 19 and 20: 2.3. Independence. When desiring to
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answering that question is extremel
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IIIV. N. TutubalinThe Boundaries of
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periodograms. It occurred that work
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at point x = 1. However, preceding
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He concludes that since the action
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The verification of the truth of a
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In the purely scientific sense this
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ought to learn at once the simple t
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the material world science had inde
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values of (2.1) realized in the n e
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*several dozen. The totality µ ica
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Mendelian laws. It is not sufficien
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example, the problem of the objecti
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a linear function is not restricted
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258 - 82 - 176 cases or 68.5% of al
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The Framingham investigation indeed
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or, for discrete observations,IT(ω
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What objections can be made? First,
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eliability and queuing are known to
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Kolman E. (1939 Russian), Perversio
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measurement is provided. Recently,
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which means that sooner or later th
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The foundations of the Mises approa
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A rather subtle arsenal is develope
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4.3. General remarks on §§ 4.1 an
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BibliographyAlimov Yu. I. (1976, 19
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processes are now going on in the s
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obtaining a deviation from the theo
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VIOscar SheyninOn the Bernoulli Law