Sampling In Statistics
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Sampling In Statistics
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Post Icon Sampling In Statistics


Sampling is a statistical technique which is used in almost every field in order to collect information and on the basis of this information inferences (results) about the characteristics of a population are made. The numerical values (e.g. mean, standard deviation etc.) calculated from the population is calledparameter. And the numerical values which is calculated from the samples is called statistic.

A statistical population (or universe) is defined as the aggregate or totality of all individual members or objects, of some characteristics of interest. For example, the population of a city, the number of students in a school, the number of items in a lot, etc. the individual members of the population are called sampling unit or simply units.

Sample is the small part chosen from the population, having the samecharacteristics as population. Sample is a small part which is representing the population. For example, if we want to check the quality of rice in a sack of 100 Kg, we take a small part from it and check the quality of rice.

It is the procedure in which we select the sample from a population. The two basic purposes of sampling are (i) to provide sufficient information about the characteristics of a population, and (ii) to find the reliability of the estimates derived from the sample.

  1. Sampling save money as it is much cheaper to collect the information from sample then from population.
  2. Sampling saves a lot of time and energy.
  3. Sampling provides information that is almost as accurate as that obtained from a complete census.
  4. The results of the causes inquiring are sometimes checked on sample basis.
  5. In certain circumstances, because of characteristics of the universe, it is only method that can be used.
  6. Sampling gives us detailed information about the population.
  7. Sampling is extensively used to obtain some of the census information.
  8. The most important advantage of sampling is that it provides a valid measure of reliability for the sample estimates.

  1. If the sample is not representative of the universe, correct inferences cannot be drawn.
  2. Some times the sample may not representative because of reason like inadequate size d sample or wrong method of sampling.
  3. When the sampling technique is used, services of experts are necessary.


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03-26-2014 06:41 PM
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