In research, the sampling methods can be broadly divided into the following two categories:

**Probability Sampling**

It is that sampling method which is mostly used in the quantitative research. The reason behind for choosing the probability sampling methods in quantitative research is that quantitative research needs a larger sample size for measurement. The probability sampling methods provide the chances of all the elements of the population for the sampling process. under the probability sampling methods following are the types of sampling methods:

- Simple random sampling

In quantitative research, it is the most popular methods of sampling. Under this type each and every individual of the population has an equal chance of being included in the sample. under the random sampling methods at first the population is defined and the sample frame is developed for the selection of the sample. Each unit is considered so that every unit in the population have a certain probability of selection. then the methods of selection are determined for the selection of the sample. the method may be lottery, tabular or the computer programming methods. Nowadays, the internet is used for collection of data using the questionnaire tools for data collection. Thus, simple random sampling methods are gaining popularity in survey research.

- Systematic sampling

It is used as an alternative to the simple random sampling method. it is used to remove the disadvantages of simple random sampling methods. For the larger population, the simple random sampling seems complicated. In this case, the systematic random sample is appropriate methods for sampling. Under this method, at first, the sample frame is developed then different groups are formed. for the selection of samples only the first group is used and an element of that group is selected at random and remaining units are pick using the arithmetic progression. while developing the sample framework at first a serial number should be assigned to all population element. Then, Identify the skip interval (K) then draw a sample by choosing every k th entry. The sampling ratio (K) should be computed using the following formula:

K=* N (population)/*n (sample size)

- Stratified sampling

This method is appropriate when the population element are homogeneous in nature. In this method, different groups are formed using the homogeneous character of the element of the population. it is also appropriate when the population is heterogeneous. in case of the heterogeneous population at first whole elements are divided into the homogeneous group on the basis of certain criteria and each group is called strata. the criteria may be sex, literacy, socio-economic class, employment etc. and double criteria. Then the needed sample is selected from stata using either simple random sampling methods or systematic random sampling methods. With the ideal stratification, each stratum is homogeneous internally and heterogeneous with other stata.

- Cluster sampling

A cluster sampling is a method where at first the population is divided into groups. Each group is called a cluster. The cluster is developed in such a way that the characteristics with the clusters are heterogeneous and between the clusters are homogeneous. Then clusters are selected randomly, which are representative of the population as a whole. the reason behind this sampling is it is economic efficiency than by simple random sampling and frequent unavailability of a practical sampling frame for individual elements. for the use of this methods the research must consider homogeneous of the cluster, equal-size or unequal-size clusters, size of the cluster, single stage or multistage cluster and need of sample size.

- multistage sampling

Under this method, sample units are sampled out in different stages. First of all, 1st stage units are sampled by some criteria (simple random or systematic). Then 2nd sampled units are sampled from the 1st sample stage again by the same criteria as in the 1st stage or by different criteria.

**Non-probability sampling**

It is that sampling method which is mostly used in the qualitative research. The reason behind choosing the non-probability sampling methods in qualitative research is that it needs a small sample size for data collection. The non-probability sampling methods do not provide the chances of all the elements of the population for the sampling process. in this sampling method, the researcher only considers the certain elements for choosing the sample for research. Following are the common types of non-probability sampling method:

- Quota sampling

In this sampling technique at first control categories or quotas of the population is set and then sample elements being selected on convenience or judgment sampling methods. In a simple word at first, the different quota is assigned to elements of the population which is considered as groups of elements. This method fixed the subgroup of the total population based on the total number of each group of the population then sampling is done through the connivance bases.

- Judgmental/ Purposive sampling

Under this sampling type, the researcher selected the sample subjectively by using his or her judgment about some appropriate characteristic required of the sample member. It involves the choice of a subject who is most advantageously placed or in the best position to provide the required information. This sampling method is appropriate when the researcher knows the elements quite well. It is suitable to research if elements under consideration are small for research for choosing samples. The selected sample for the specific purpose, even if this makes a sample less than fully representative. The choice of the item in the sample depends upon the judgment of the investigator.

Under purposive sampling, elements are chosen based on the purpose of the study or the objective of the study. Purposive sampling may involve studying the entire population of some limited group or a subset of a population. Purposive sampling does not produce a sample that is representative of a larger population, but it can select the clearly defined and relatively limited group.

- Convenience sampling

Under this method, samples are selected not by judgment or probability techniques because the elements in a fraction of the population can be reached conveniently. It refers to collect the information from the members of the population who are conveniently available to the researcher. This types or sample is mainly used during the exploratory phase of research. This method is the best way of getting some basic information quickly and efficiently.

- Snowball sampling

It is defined as having all the persons in a group or organization identified their friends. This sampling is used for obtaining an impression of informal social relationships among individuals.

In snowball sampling method the researcher identifies one member of some population of interest, then slowly reach to the other member from the information supplies by previous member and the process continue till the sample size is complete.

Snowball sampling is very good for cases where members of a special population are difficult to locate. The method also has an interesting application to group membership – if you want to look at the pattern of recruitment to a community organization over time, you might begin by interviewing fairly recent recruits, asking them who introduced them to the group. Then interview the people named, asking them who recruited them to the group.

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