Definition of Stratified Sampling
Stratified Sampling is defined as a Sampling Methodology that can be applied onto the population. It is the methodology of dividing members of a particular population into numerous homogeneous subgroups before sampling. In this case, each element of the population must be assigned to only a single stratum. Here, the strata should also be exhaustive in a collected manner which means that no element of the population can be excluded.
In Computational Statistics, Stratified Sampling is seen as a methodology of Variance Reduction when Monte Carlo Procedures are utilized in order to estimate population statistics from a known population.
Textbooks on Stratified Sampling
There are a number of textbooks on Stratified Sampling Methods for marketers to follow. Details of some interesting textbooks have been stated as follows:
- Model Assisted Survey Sampling by Carl-Erik Sarndal and Bengt Swensson (Published by Springer Science & Business Media – Year 2003).
- Advanced Sampling Theory With Applications: How Michael ""Selected"" Amy by Sarjinder Singh (Published by Springer Science & Business Media – Year 2003).
Examples of Stratified Sampling
Example 1: An interesting example of Stratified Sampling can be its utilization in scanning the entire staff of a particular organization. This can be done on the basis of some specific parameters like Gender, Hours of Duty alias Job Type and Age. When such parameters are taken into consideration then, proportional allocation is carried out, and the result is derived.
Example 2: Another example of Stratified Sampling can be its utilization in political surveys. Marketers may utilize the Stratified Sampling by observing the particular population in terms of various groups on the basis of Religion, Race or Caste. Then they can proceed further with the Stratified Sampling procedure.
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