Sampling –The Core of Statistics

Study of large populations has been made possible only through the application of appropriate sampling techniques as studying the population through census method is impossible, in most cases. Appropriate sampling technique refers to the ability to pick out a representative sample from an entire universe of elements under study within the existing constraints; constraints can arise due to limitations on costs, time and resources. The effectiveness of sampling technique is gauged by how accurately the sample represents the population. Various characteristics of the sample obtained by the application of mathematical and statistical concepts as various formulae can be adjusted for the entire population. The formulae also allow for calculation of error margins under different conditions.

Past exposure to sampling enables researchers to determine the best fit sample design with ease. Researchers can maintain a record of successful sample designs and repeat them or manipulate them for future use. Sample design implies the plan for obtaining a sample from a given universe; the plan mentions the techniques and procedures to be followed for obtaining the sample. For drawing a sample first of all a sample frame has to be worked out keeping in mind the research problem, samples drawn from incorrect sample frames yield erroneous results. Sample design decisions include decisions on sampling unit for example a family, a school can serve as a sampling unit; sample size that is the number of units in a sample and sampling procedure.

Depending upon the situation the researcher can choose from a number of sample procedure options such as Probability sampling including simple random and complex random sampling, the latter includes cluster, systematic and stratified sampling. Non probability sampling methods like convenience, quota and judgment sampling can also be applied depending upon the requirements.