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.
ADVANTAGES OF SAMPLING
DISADVANTAGES OF SAMPLING
- Sampling save money as it is much cheaper to collect the information from sample then from population.
- Sampling saves a lot of time and energy.
- Sampling provides information that is almost as accurate as that obtained from a complete census.
- The results of the causes inquiring are sometimes checked on sample basis.
- In certain circumstances, because of characteristics of the universe, it is only method that can be used.
- Sampling gives us detailed information about the population.
- Sampling is extensively used to obtain some of the census information.
- The most important advantage of sampling is that it provides a valid measure of reliability for the sample estimates.
- If the sample is not representative of the universe, correct inferences cannot be drawn.
- Some times the sample may not representative because of reason like inadequate size d sample or wrong method of sampling.
- When the sampling technique is used, services of experts are necessary.