Page 61 - SREENARAYANAGURU OPEN UNIVERSITY

2.1.3 Sampling Theories

There are two fundamental principles that play an important
role in understanding the behaviour of population. They are Law
of Inertia of Large Numbers and the Law of Statistical Regularity.

2.1.3.1 Law of Inertia of Large Numbers
The law of inertia of large numbers states that as the sample ◆ Sample convergence
size increases, the sample mean becomes closer to the population
mean. The Law of Inertia of Large Numbers suggests that when
we analyse a larger sample, the individual variations will have
only a less influence on the overall result. Thus, we get a more
reliable estimate or average that reflects the true characteristics of
the entire population we are studying.

2.1.3.2 Law of Statistical Regularity

The statistical regularity principle states that if on an average
the sample chosen is a random one, the sample will have the
same composition and characteristics as the universe. The
statistical regularity principle in sampling is a concept in statistics
that says when we take a random group of items from a larger ◆ Randomness and
group, the smaller group will typically have similar patterns and representativeness
characteristics as the larger group. This principle forms the basis for of sample
various statistical inference techniques used in research and data
analysis. This is the reason why random sampling is considered as
the best technique of selecting a representative sample. Statistical
regularity implies that certain statistical properties observed in the
sample, such as means, variances, or correlations, are likely to
approximate the corresponding parameters of the population. This
assumption allows researchers to make generalisations or draw
inferences about the population based on the observed sample
data.

2.1.4 Sampling Techniques

There are two types of sampling techniques:

◆ Random Sampling or Probability Sampling
◆ Non- Random Sampling or Non-Probability Sampling

SGOU - SLM - MCom Research Methodology 55