Sampling Design

Sampling Design: A sampling design is a definite plan for obtaining a sample from the sampling frame. Population frame or sampling frame is the listing of all items in the population with proper identification. The list of names and addresses of workers are called sampling frames if we want to find out the capital invested and the number of workers working in chemical industries in Pimpri. Sampling design is a technique of selecting items for the sample. There are many sample designs from which a researcher can choose a specific and most appropriate design. While developing a sampling design, the researcher must consider the following parameters.

Universe or Population:

The first step in developing any sample design is to clearly define the set of objects or universe. The universe can be finite or infinite. The population contains a fixed number of items so that it is possible to list it in its totality, it is called finite population. e.g. total population of the village, workers working in a small unit, etc. The population where we cannot make out the total number of items is called an infinite population, e.g. number of stars in the sky. observers of a cricket match, etc.

Sampling Unit:

A final decision has to be taken concerning a sampling unit before selecting a sample. Sampling units may be geographical units (state, district, town, etc.), social units (schools, family, etc.), or construction units (flat, house, etc.). The researcher has to select one or more: such units for his study.

Sampling Frame or Source List:

The sampling frame is a list of elements in the population from which the sample is drawn. It contains the names of all items of a universe. The researcher has to prepare a comprehensive, correct, and reliable list if the source list is not available. The source list may be a polling list, telephone directory, maps, publications of the government, chamber of industries, etc.

Sample Size:

The size of a sample refers to the number of items to be selected from the universe to constitute a sample. The size of the sample should be optimum, neither be excessively large, nor too small. An optimum sample fulfills the requirements of efficiency, representativeness, and reliability. The researcher must consider the different parameters before deciding the sample size such as size population, homogeneity or heterogeneity of the universe, nature of the study, type of sampling, the standard of accuracy, cost, etc.

Sampling Method:

Sampling design is based on the method of samplings such as probability or random sampling and non-probability or purposive sampling. The choice of method depends upon the nature of the problem, standard of accuracy, availability of sampling frame, time, cost, and other constraints.

Budgetary Constraint:

The researcher has to keep the cost in mind while preparing a sample design. Budget for sampling has a major impact not only on the size of the sample but also on the type of sample. This fact can even lead to the use of a non-probability sample.

Sampling Plan:

It involves specifying how the sampling plan is going to be put into operation. It consists of instructions for the actual implementation of the sampling plan and instructions to the interviewers regarding how to select a random sample.

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