Concept of Sampling Methodologies and Their Applications

Abstract

AbstractAs complete enumeration of a population is very often untenable because of time, cost and various other constraints, a part of the population is studied to draw inferences on the population; and this process is known as sampling. According to Mildred Parton, ‘Sampling method is the process or know-how of drawing a definite number of the individuals, cases or the observations from a particular universe, selecting part of a total group for investigation’. The advantages of sampling are very accurate, reliable, consuming less time and economical. Sampling has also some disadvantages, such as inadequacy of the samples, chances for bias, problems of accuracy, difficulty in representative sample, chances of sampling errors, etc. Population is defined as the collection of all individuals or items of a particular characteristic of interest in a certain geographical area, and sample is a subset of the population. In some research trials, it may be possible to take the measurement of all the objects, but most of the time, monitoring the entire population becomes too costly and time-consuming. For example, catching and measuring length and weight of 40 fishes or 80 fishes individually from a few experimental tanks is possible, but catching 500 fishes from a big pond or reservoir and measuring their length and weight is difficult. When it is supposed to find the average weight of fish in a big pond or reservoir, which is impossible, then manageable portions of the population are taken as a sample. Sample numbers vary widely and depend upon the population situation, e.g. 1%, 5%, 10%, 25% or even more. The larger sample size provides the higher accuracy and reliability, but simultaneously it also increases the cost. So, sample size should be minimal but taken randomly so that all individuals of the population have an equal chance of being selected and represent the population. The distinct proper sampling techniques are followed to make the samples representative of the population in different situations. There are two types of sampling: non-probability sampling and probability sampling. Non-probability sampling is a sampling technique where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected, e.g. convenience sampling, purposive or judgemental sampling, etc. Probability sampling is a sampling technique where the samples are gathered in a process that gives all the individuals in the population equal chances of being selected, e.g. random sampling, stratified sampling, systematic sampling and cluster sampling.