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" "The next point to which I turned my attention was the frequency with which the several numbers themselves occurred. ...Each number might be expected to have occurred either 447 or 448 times. ... I found that they fitted to a standard deviation of 15.85 while the theoretical standard was 20.87 giving a difference of 5. ...What is a reasonable amount for the standard deviation of an experiment of this kind to differ from its theoretical value..? The mathematician answers... by finding the standard deviation of the standard deviation. It turned out... to be 2.43... the odds against a divergence as large or larger than 5...were ...21 to 1. In every two years I might expect such a deviation from the most probable results to occur once. ...I ...increased ...by counting the numbers for each week in the month instead of the total month. Here the experimental standard deviation [was] 7.2, the theoretical being 10.34, a difference of 3.14, while the standard deviation between experiment and theory was only 0.60. The odds against a divergence so great as this are... about 2,000,000 to 1.
Karl Pearson (27 March 1857 – 27 April 1936) was an influential English mathematician and biostatistician. He founded the world's first university statistics department at University College London in 1911.
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I determined to... investigate how closely the runs, that is, successions of numbers of the same colour were in accord with theory. ...The chance of a head<math>=\frac{1}{2}</math>, of two heads succeeding each other <math>\frac{1}{2}\times\frac{1}{2} = \frac{1}{4}</math>, of three heads <math>\frac{1}{2}\times\frac{1}{2}\times\frac{1}{2} = \frac{1}{8}</math>, and so on. Calling a "set" the run of tosses or the throws of the roulette ball till a change of face or of colour comes, the chance of a change<math>=\frac{1}{2}</math>, of a persistence followed by a change <math>\frac{1}{2}\times\frac{1}{2} = \frac{1}{4}</math>, and so on. ...[I]n the case of the roulette on one occasion the actual deviation is nearly ten times the standard.... The odds are thousand millions to one against such a deviation as nine or ten times the standard. ..My pupil... tabulated... the runs in a second fortnight's play with the result... so improbable that it was only to be expected once in 5000 years of continuous roulette. ...Finally, Mr. de Whalley investigated 7976 throws of the ball, forming a fortnight's play, at a slightly later date... There resulted deviations 4.63, 4.62, and 4.44 times the standard deviation, or odds of upwards of 263,000 to 1... That one such fortnight of runs should have occurred in the year 1892 might be looked upon as a veritable miracle, that three should have occurred is absolutely conclusive. Roulette as played at Monte Carlo is not a scientific game of chance.
The purpose of the mathematical theory of statistics is to deal with the relationship between 2 or more variable quantities without assuming that one is a single-valued mathematical function of the rest. The statistician does not think a certain x will produce a single-valued y; not a causative relation but a correlation. The relationship between x and y will be somewhere within a zone and we have to work out the probability that the point (x,y) will lie in different parts of that zone. The physicist is limited and shrinks the zone into a line. Our treatment will fit all the vagueness of biology, sociology, etc. A very wide science.
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