Introduction
This synopsis is a discussion on sampling in research. It is mainly designed to equip beginners with knowledge on the general issues on sampling that is definition of sampling, the purpose of sampling in research, sample, and its characteristics. Sampling method is an important tool in the realm of social science researches. For this, the data has to be collected and analysed. There are two methods of data collection, i.e., Census Method and Sampling Method. For studying any problem it is impossible to study the entire population. It is therefore convenient to pick out a sample out of the universe proposed to be covered by the study. For a clear flow of ideas, a few definitions of the terms used are given.
What is a sample?
According to Webster Dictionary, 1985
“A sample is a finite part of a statistical population whose properties are studied to gain information about the whole.”
Goodeand Hatt defined sample as “a smaller representation of large whole.”
Nan Lindefines it as “asubject of cases from the population chosen to represent it.”
So we can say that when a small group is selected as representative of the whole it is known as sample.
What is sampling?
The sampling method was first introduced and used in a social research in 1754 A.D. by Bowley. Sampling is the act, process, or technique of selecting a suitable sample, or a representative part of a universe or population for the purpose of determining parameters or characteristics of the whole population. It is the process of selecting a sample from the population. For this population is divided into a number of parts called Sampling Units.
Universe or Population:
In research these term used interchangeably. Generally universe is a geographical area from where sample is to be collected. Population is constituted of all the individuals, things, events, documents or observations etc. belonging to a designated category, which a particular study should principally cover. A population contains sub-population or stratum.
What is the purpose of sampling?
To draw conclusions about populations from samples, we must use inferential statistics which enables us to determine a population`s characteristics by directly observing only a portion (or sample) of the population. We obtain a sample rather than a complete enumeration (a census) of the population for many reasons. These are as follows:-
- Economy
- Reliability
- Detailed study
- Scientific base
Characteristics of an ideal sampling:
Sampling has following characteristics:
- Representativeness- An ideal sample must be such that it represents adequately the whole data. We should select those units which have the same set of qualities and features as are found in the whole data.
- Independence-The second feature of a sample is independence that is interchangeability of units. Every unit should be free to be included in the sample.
- Adequacy-The number of units included in sample should be sufficient to enable derivation of conclusions applicable to the whole data.
- Clear, unambiguous and definite.
- Selected on the basis of mathematical law of chance or probability.
- Sample should represent the different areas of universe.
Conclusion:
In conclusion, it can be said that sampling technique has very high value in the educational, economic, commercial and in day-to-day activities. Using a sample in research saves mainly money and time, if a suitable sampling strategy is used. If appropriate sample size selected and necessary precautions taken to reduce on sampling and measurement errors, then a sample should yield valid and reliable information.
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