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On a New Method of Graduation

Published online by Cambridge University Press:  20 January 2009

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Suppose that as a result of observation or experience of some kind we have obtained a set of values of a variable u corresponding to equidistant values of its argument; let these be denoted by u 1, u 2, … un If they have been derived from observations of some natural phenomenon, they will be affected by errors of observation; if they are statistical data derived from the examination of a comparatively small field, they will be affected by irregularities arising from the accidental peculiarities of the field; that is to say, if we examine another field and derive a set of values of u from it, the sets of values of u derived from the two fields will not in general agree with each other In any case, if we form a table of the differences δu 1 = u 2u 1, δu 2 = u 3u 2, …, δ2 u 1 = δu 2 − δu 1, etc., it will generally be found that these differences are so irregular that the difference-table cannot be used for the purposes to which a difference-table is usually put, viz., finding interpolated values of u, or differential coefficients of u with respect to its argument, or definite integrals involving u; before we can use the difference-tables we must perform a process of “smoothing,” that is to say, we must find another sequence u 1′, u 2′, u 3′, …, un ′, whose terms differ as little as possible from the terms of the sequence u 1, u 2, … un , but which has regular differences. This smoothing process, leading to the formation of u 1′, u 2′ … un ′, is called the graduation or adjustment of the observations.

Type
Research Article
Copyright
Copyright © Edinburgh Mathematical Society 1922

References

* The theory may be extended to the case when the observations are not taken at equidistant values of the argument, by taking instead of S the sum of the squares of the third divided differences of the graduated values.

* If this is not the case, we graduate some function of u, such as log u, instead of u, choosing this function so that its measure of precision has nearly the same value for all values of the argument.