Characteristics of a Good Sample

Characteristics of a Good Sample: Sampling is an important part of all scientific research and it is well developed in biological, physical, chemical, and social sciences. Sampling is a process of obtaining information about the entire population by examining only part of it. A sample is a part of the population that is studied to make inferences or conclusions about the whole population.

The total or the aggregate of all units that conform to some designated set of specifications is called the universe or population. A population may be a group of people, students, workers, customers, voters, houses, etc. The specific nature of the population depends on the purpose of the investigation. Each entity (student, person, family) from the population about which information is collected is called a sampling element. The sampling frame is the complete list of all elements or units from which the sample is collected e.g. list of patients, list of students, etc.

Sampling is based on the law of statistical regularity and the law of inertia of large numbers. The first law states that the small numbers of items (sample) are picked from a large number of items (universe or population), the sample will tend to possess the same characteristics as that of a whole group of items. The second law of inertia states that the sample should be large enough to represent truly the entire population of the universe.

While collecting primary data, the information may be obtained either by the census method or the sampling method. In the census method, every functional unit of the population or group is studied. This method will provide more reliable and accurate results but, it requires more time and money compared to the sampling method. In the sampling method, only a small part of the whole population is to be studied and the conclusions apply to the whole population.

If the sample results are to be worthwhile, a sample must possess the following essentials.

The characteristics of a good sample are:

  • An ideal sample must be representative of the population corresponding to its properties. It should not lack in any characteristic of the population.
  • It must be unbiased and must be obtained by a probability processor random method.
  • It must make the research work more feasible and has the practicability for the research situation.
  • It must yield an accurate result and does not involve errors. The probability of error can be estimated.
  • Sample must be adequate to ensure reliability. A sample having 10% of the whole population is generally adequate.
  • The sample must be comprehensive. It is a quality of sample which is controlled by the specific purpose of the investigation.
  • Sample units must be chosen systematically and objectively.

The important advantages are as follows:

  • Sampling techniques bring about cost control of research projects. It is less expensive to collect data from a portion of the population than from the entire population.
  • The researcher can collect more elaborate information from the few sample units than from the large population. Multiple approaches can be applied to a sample for an intensive analysis.
  • The sampling technique has greater adaptability, precision, and accuracy in the observation.
  • Sampling techniques is a scientific method because the conclusion derived from the study of certain units can be verified from other units. The deviations can be seen from average.
  • The sampling technique helps the researcher to complete the project in a short duration. Researchers can save time and utilize it for other research studies.
  • The examination of a few sample units is sufficient. Hence, it has wide applicability in most situations or research studies.

The limitations of sampling techniques are as follows:

  • Sampling is not feasible. the population is needed. the situation where precise knowledge about each unit of population is needed.
  • The sampling technique can be successful only if the researchers have the basic and specialized knowledge, understanding, and experience.
  • Sampling does not give the accuracy available from the census. It is less accurate than the census method.
  • The accuracy and reliability of sample data are affected by sampling errors and data collection errors.
  • If the units in the field of the survey are liable to change then the sampling technique will be very hazardous. It is not scientific to extend the conclusions derived from one set of samples to other sets which are dissimilar.
  • If sampling is done on a partial basis, then it can not expect the results true, neutral, and impartial.
  • Selection of representative sampling from social and political units may differ. If the sample will not give correct representation, then its finding will be less reliable and authentic.
Make sure you also check our other amazing Article on : Sampling and Non-Sampling Errors
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