A sample as the name suggests is a smaller representation of a larger whole. The investigation of a phenomenon in complete detail would involve such a mass of data that analysis would be slow and tedious. Therefore, spending many hours over the analysis of mass material form one point of view, researcher may use that time to examine smaller amount of material from many point of view or can pursue more intensive analysis of fewer cases.
Thus, when the population is relatively large and physically not accessible or difficult researchers survey only a sample. A sample is a portion of people drawn from a larger population. A sample represents the population as it has the same basic characteristics of the population form which it is drawn.
2.It offers high degree of accuracy because it deals with a small number of persons.
3.In a short period of time valid and comparable result can be obtained with the help of sampling.
4.Sampling is less demanding in terms of requirements of investigator since it requires a small portion of the target population.
5.It is economical since it contains fewer people.
Essentials of sampling:
If the sample results are to have any worthwhile meaning it is necessary that a sample possesses the following essentials.
- Representativeness: A selected sample should be selected in such a way that it truly represents the universe, otherwise the results obtained may be misleading.
- Adequacy: The size of sample should be adequate otherwise it may not represent the characteristics of the universe.
- Independence: All items of the sample should be selected independently of one another and all items of the universe should have the same chance of being selected in the sample.
- Homogeneity: Homogeneity means there should be no basic difference in the nature of units of the universe and that of the sample.
Type of Sampling:
There are basically two type of sampling :
probability sampling and non-probability sampling. Probability sampling is one in which every unit of the population has an equal probability of being selected for the sample, the researcher have complete information about the universe of the study. Non probability sampling makes no claim of representativeness as every unit does not get the chance of being selected it is the researcher who decides which sample unit should be chosen it is applied in the research situations where there is no list of person to be studies.
Probability sampling is considered to be the primary method of selecting the sample. According to Black and Champion (1976) the probability sampling requires following conditions to be satisfied
(1) Complete list of subjects to be studies is available
(2) Size of the universe must be known
(3) desired sample size must be specified
(4) each element must have an equal chance of being selected.
There are six forms of probability sampling: Simple random, stratified random, systematic (or interval), cluster, multi stage and multiphase.
1.Simple random sampling: – Simple random sampling refers to that sampling technique in which each and every unit of the population has an equal opportunity of being selected in the sample. In simple random sampling which item get selected in sample is just a matter of chance, personal bias of the investigator does not influence the selection. To ensure randomness of selection one may adopt either the lottery method or consult tippets table.
Lottery method: This is very popular method of taking a random sample. Under this method all items of the universe are numbered or named on separate slips of paper of identical size and shape. These slips are then folded and mixed up in a container or drum. A blindfold selection is then made of number of slips required to constitute the desired sample size. The selection of items thus depends entirely on chance.
Tippets table or table of random numbers:- The lottery method becomes quite unmanageable as the size of population increases. An alternative method of random selection is that of using the table of random number or tippets table. In the tippets table random number are generally obtained by some mechanism which when repeated at large number of times, ensures approximately equal frequencies for the number from 0 to 9 and also proper frequencies for various combinations of numbers (such as 00, 01, ….999 etc.) that could be expected in a random sequence of the digit 0 to 9.
2.Stratified random sampling:-This is the form of sampling in which the population is divided into strata or sub groups and a sample is drawn from each stratum. These sub samples make up the final sample of the study.
There are two types of stratified sampling: – Proportionate and disproportionate random sampling. Proportionate random sample is one in which the sample unit is proportionate to the size of the sampling unit while in the disproportionate random sampling sample unit is not related to the units of the target population.
3.Systematic Sampling:-In this sampling technique an initial point is selected by a random process and then every nth number from the list is selected.
4.Cluster Sampling: – This sampling implies dividing population into clusters and drawing random sample either from all cluster or selected clusters. Initial cluster are called primary sampling units, cluster within the primary cluster are called secondary sampling units and cluster within the secondary cluster are called multistage cluster. When clusters are geographic units it is called area sampling. For example dividing one city into various wards, each ward into areas, each area in to each neighborhood and each neighborhood in to lanes.
5.Multistage Sampling: – In this method, sampling is selected in various stages but only the last sample of subjects is studies for example for studying the Panchayat system in villages. India is divided into four zones south, west, east and north, then one state is selected from each zone (say Gujarat, Karla, Assam and Jammu & Kashmir), one district is selected from each state, one block is selected from each district and three Panchayat are selected from each block.
6.Multiphase Sampling: – The process in this type of sampling is same as in multistage sampling. However in multi phase sampling procedure, each sample is adequately studies before another sample is drawn from it.
Non-Probability Sampling: –
Non-probability sampling methods are those which do not provide every item of the universe with a known chance of being included in the sample.
Judgment Sampling: – It is also called purposive sampling. In this method of sampling the choice of sample items depends exclusive on the judgment of the investigator for example if the researcher wants to study the child labourers. He knows the areas where the child labourers are found in abundance. He will visit only these areas and interviews child labourers of his choice and convenience.
Convenience Sampling: – This is also known as ‘accidental’ or ‘haphazard’ sampling. In this sampling the researcher studies those persons who are most conveniently available to him or who accidentally come in his contact during research investigation.