Sunday, April 27, 2014

LAW OF STATISTICAL REGULARITY

This principle signifies the representative character of the sample. The law of statistical regularity indicates that a moderately large number of items chosen at random from a large group are almost sure to possess, on an average, the characteristics of the large group.
A sample properly drawn from a population within certain variable limits reveals the characteristics of that population, even though the number of items in this sample is small as compared with the number of items in the population. There are two qualifying conditions for application of this law:

 (i) The selection of the sample is purely on a random basis, in the sense that the sample shall not be drawn with the help of non-probability sampling techniques.  When we say that the sample shall be drawn ‘properly’ this implies systematic application of probability criteria,

(ii) The results of the sample reveal, on an average, the behavior of the population. This signifies the facts that the sample estimates are within the prescribed limits to establish the fact that these estimates are equal to the population parameters. If these conditions are satisfied, it is possible for one to depict fairly accurately the characteristics of the population by studying only part of it.

The theory of probability tells us of the mathematical expectation of happening or the failure of event and on this basis the law of statistical regularity tells us that random selection from the universe is likely to give a representative character. It may be noted that different samples drawn from the universe would not yield the same results.  However, the probable error diminishes with an increase in the number of items taken in the sample.  As the size of the sample increases, the reliability of the results also increases.
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