What is Sampling? A most critical issue in the survey method is the identification of subjects to whom the instrument will be administered or questions will be asked. Those people are typically called a sample, which means is known a group as their subjects drawn from some larger group. This larger group population that includes all the people, objects or events of a particular class.
When any sample accurately reflects the characteristics of a certain population, it is called a representative sample. Surveys generally involve sampling. Careful choice of a survey sample permits researchers to generalize findings from the sample to the population. A sample is chosen from the sampling frame. The ability to generalize from a sample to the population depends critically on the representativeness of the sample. A biased sample will affect the results; so sample should be free of any bias. If the characteristics of the sample are systematically different from the characteristics of the population, that is considered as bias sample. Individuals in a population differ in many ways and in turn, populations differ from each other.
TYPES OF SAMPLING
Two major types of samples can be drawn i.e.
- probability samplings
- non-probability samplings
PROBABILITY AND NON-PROBABILITY SAMPLINGS
Sampling methods may be classified into two types, probability samplings, and Non-probability samplings. When each element in the populati0n (universe) has a known probability of its being included in the sample, the sampling is said to be probability sampling. Simple Random sampling, Stratified, Random sampling, Systematic sampling, etc. are the important examples of probability sampling.
In non-probability sampling, the selection of the elements is not based on probability theory but the personal judgment plays a significant role in the selection of the sample. the examples of non-probability sampling are the Judgment Or Purposive sampling, Quota sampling, etc,
Stratified Random Samplings
sometimes, a population contains highly variable material and a simple random sample fails adequately represent the population. The population is then divided into a number of mutually exclusive groups of units in such a way that the units within each group are as similar as possible.This process of dividing the population is called stratification, the groups are called strata. Simple random samples from each of the strata are then selected and combined into a single sample. This technique is called the Stratified random sampling.
This is a technique in which samples are drawn according to some predetermined pattern. The units are selected by the equally spaced interval, known as samplings interval. Strictly speaking, this technique is not truly random, because the subsequent units are pre-selected by the constant samplings interval.
This is a process of sampling in which the samplings units are to be found in “groups” of individuals. These groups are known as clusters. Each cluster is treated as a single unit in the selection process. A sample of clusters is selected at random. Sometimes, the clusters relate to geographical regions, then the sampling is known as area samplings.
A non-probability sample is also called a judgment sample as the personal judgment plays a significant part in the selection of the sample. The two commonly used types of judgment samplings are the Purposive samplings and the Quota samplings. They are briefly described below;
This is a technique in which the selection of a sample is made by some purposive method. Here the investigator may give rein to his inclinations in selecting a sample.
A Quota sample is a type of non-probability or judgment sample in which the information collected from the specified number of individuals, i.e., the quotas of the population, e.g. the quotas of old and young; urban and rural; upper, middle and lower income group, etc. Quota sampling, is a very quick form of investigation, is widely used in public opinion polls and market research survey.