Like any other discipline the science of statistics has certain laws to be followed by its users. They are:

*(i)* The Law of Statistical Regularity and *(ii) *The Law of Inertia of Large numbers. These two laws are explained here as under:

#### (i)** The Law of Statistical Regularity.**

** **This law providers “that a moderately large number of items chosen at random from a large group are almost sure on an average to possess the characteristics of the large group.”

This law has emerged from the mathematical theory of probability. The pith and substance of this law is that the behaviour of an individual event may be erratic and imponderable but when a large number of events of same category are considered, a stable behaviour emerges. According to this law, statistical data, if the number of observations is not very large. As such, the statistical techniques like averages, dispersions, coefficient of skewness, coefficient of correlation, regression analysis, etc. provide estimates of the characteristics of the population but not of the individual members. It is on the basis of this law that an insurance company estimates the insurance claims payable during a particular period to the heirs of the policyholders who are expected to die in that period.

This law is founded upon the fact that many forces play in a phenomenon and that if the observations are large, the typical or odd behaviour or any one gets neutralised by the typical or odd behaviour of some one on the other extreme.

#### (ii) **The Law of Inertia of Large Numbers.**

This law provides “that other things remaining the same, as the sample size increases, the results tends to be more reliable and accurate.” This law is a corollary to the previous law of statistical regularity. According to this law, in a large mass of data, the characteristics of the extreme items will be counter balanced and the general characteristics will be ultimately reflected. In the words of A.L.Bowley, “Great numbers and averages resulting from them such as we always obtain in measuring social phenomena have a great phenomenon.”