Explain briefly the types of sampling.

Q. Explain briefly the types of sampling.




The sampling techniques may be broadly classified into

  1. Probability sampling
  2. Non-probability sampling

Probability Sampling:

Probability sampling provides a scientific technique of drawing samples from the population. The technique of drawing samples is according to the law in which each unit has a probability of being included in the sample.

  • Simple random sampling

Under this technique, sample units are drawn in such a way each and every unit in the population has an equal and independent chance of being included in the sample. If a sample unit is replaced before drawing the next unit, then it is known as simple Random Sampling with Replacement. If the sample unit is not replaced before drawing the next unit, then it is case, probability of drawing a unit is 1/N, where N is the population size. In the case probability of drawing a unit is 1/Nn.

  • Stratified random sampling

This sampling design is most appropriate if the population is heterogeneous with respect to characteristic under study or the population distribution is highly skewed.

Table: Merits and demerits of stratified random sampling



1. Sample is more representative 1. Many times the stratification is not effective
2. Provides more efficient estimate 2. Appropriate sample sizes are not drawn from each of the stratum
3. Administratively more convenient
4. Can be applied in situation where different degrees of accuracy is desired for different segments of population
  • Systematic sampling

This design is recommended if we have a complete list of sampling units arranged in some systematic order such as geographical, chronological or alphabetical order.

Table: Merits and demerits of systematic sampling



1. Very easy to operate and easy to check. 1. Many case we do not get up-to-date list.
2. It saves time and labour. 2. It gives biased results if periodic feature exist in the data.
3. More efficient than simple random sampling if we have up-to-date frame.
  • Cluster sampling

The total population is divided into recognizable sub-divisions, known as clusters such that within each cluster they are homogenous. The units are selected from each cluster by suitable sampling techniques.

  • Multi-stage sampling

The total population is divided into several stages. The sampling process is carried out through several stages.

 Figure: Multistage sampling Figure: Multistage sampling

Non-probability sampling:

Depending upon the object of inquiry and other considerations a predetermined number of sampling units is selected purposely so that they represent the true characteristics of the population.

  • Judgment sampling

The choice of sampling items depends exclusively on the judgment of the investigator. The investigator’s experience and knowledge about the population will help to select the sample units. It is the most suitable method if the population size is less.

Table: Merits and demerits of judgment sampling



1. Most useful for small population 1. It is not a scientific method.
2. Most useful to study some unknown traits of a population some of whose characteristics are known. 2. It has a risk of investigator’s bias being introduced.
3. Helpful in solving day-to-day problems.
  • Convenience sampling

The sampling units are selected according to convenience of the investigator. It is also called “chunk” which refer to the fraction of the population being investigated which is selected neither by probability nor by judgment.

  • Quota sampling

It is a type of judgment sampling. Under this design, quotas are set up according to some specified characteristic such as age groups or income groups. From each group a specified number of units are sampled according to the quota allotted to the group. Within the group the selection of sampling units depends on personal judgment. It has a risk of personal prejudice and bias entering the process. This method is often used in public opinion studies.


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