method of sampling

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sampling W.G.Cocharn- In every branch of science we lack the resources, to study more than fragment of the phenomena that might advances our knowledge. Fragment – Sample Phenomena – Population David S.Fox- In the social sciences, it is not possible to collect data from every respondent relevant to our study but only from some fractional part of the respondents The process of selecting the fractional part is called Sampling.

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Technique of Sample Investigation In the technique of sample investigation certain units from the whole domain of survey are selected as being representative. Now these are studied in detail and conclusions arrived from these are extended to the entire or domain. Example – If we have to study the monthly expenditure of the teacher of a university. We may not study all the teachers. suppose these are 1,000 teachers; then we may collect expenditure figures of only 600 and extend our conclusions to all of them.

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Features of Sampling Technique 1.Economy – The sampling technique is much less expensive, much less time consuming. 2.Reliability – For reliability sample units is made with due care and the matter under survey is not heterigeneous. 3.Detailed study – If number of sample units is small these can be studied intensively and elaborately.

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Method Of Sampling 1.Probability sampling – It gives the probability that sample is representative of population. Technique of the probability sampling (i) Simple random sampling (ii) Systematic sampling (iii) Stratified sampling (iv) Multiple or Double sampling (v) Multistage sampling (vi) Cluster sampling

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2. Non probability Sampling In the absence of any idea of probability the method of sampling is known as non probability sampling. Types of Non-probability sample Incidental or accidental sample Purposive sample Quota sample Judgment sample

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Characteristics of Probability Sampling It refers from the sample as well as the population. Every individual of the population has equal probability to be taken into the sample. It may be representative of the population. Its observation are used for the inferential purpose. Inferential or parametric statistics are used. Its representativeness refers to characteristic. Its comprehensiveness refers to size and area.

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Characteristics of Non-Probability Sampling There is no idea of population. There is no probability of selecting any individual. It has free distribution. The observations are not used for generalization purpose. Non parametric or non-inferential statistics are used. There is no risk for drawing conclusions.

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Characteristics of A good Sample True Representative: The population is known an aggregate of certain properties and sample is called as sub-aggregate of the universe. Free from Bias: It does not permit prejudices, pre-conceptions and imagination to influence its choice. Objectivity: A good sample is an objective one. It refers to objectivity in selection procedure. Accurate: It yields accurate estimate or statistics and does not involve errors.

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Economical: A good sample is economical from energy, time. Approachable: The subject of good sample are easily approachable. The research tool can be easily administered on them and data can be easily collected. Good size: The size of good sample is such that it yields an accurate result. The probability of error can be estimated. Feasible: A good sample makes the research work more feasible. Practical: A good sample has the practicability for research situation.