Posted on: 8th Apr 2020 3098 Views

Sampling method in Research

The sampling method in research is a procedure that the researcher performs for selecting a sample from a large population. PhD scholars find selecting a sample quite a difficult task as they are not aware of the proper sampling method.

They also have confusion regarding which sampling techniques to choose for their research. Our professionals for supporting students are providing a brief explanation of different sampling methods.

Sampling method in Research

Sampling Method Definition

The sampling method is a technique through which few people from a wide population are selected as participants in research. When performing research on a group of people, it is quite difficult for an investigator to accumulate information from a large number of people.

Instead of gathering data from a large number of people, an investigator selects a sample. A sample in research can be referred to as a group of people whom you have selected as participants in your study.

1. Definition of the population in research

First, before starting sampling you need to determine the target population for your research.

The population can be referred to as a large group of people about whom you intend to conclude. You can define the population in terms of age, income, geographical location, etc.

A sample is a specific group of people from whom you want to accumulate information about the research topic.

For instance, if you are performing research for gathering information about the performance of the specific company, you can randomly select its customers or employees as participants in research.


  1. You must define the population considering the research objectives.
  2. In the case population on which you are conducting research is too large then it might be difficult for you to have access to a sample that represents the entire population.

2. Sampling frame

The sampling frame is a framework that consists of a list of a group from which you will select a sample.  In simple words, the sampling frame consists of a complete population.

Example:  A researcher is performing a study in order to analyze the working environment in an enterprise. There are approx. 1000 employees in a company. The sampling frame which the investigator has select is information with HR. The researcher will obtain a list of employees along with their contact detail from the HR department in a company.

3. Sampling Size

It is several people in the sample who are completely based on the size of the population.  The researcher can utilize the Sample Size calculator for determining the size of the sample.  The main benefit of using the sample size calculator is that you can make assumptions about the population exactly.

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What are the different types of sampling?

The selection of an appropriate technique for choosing participants is very much important. As the sampling procedure could have a significant influence on research outcomes. It is very much important to make the right selection of samples to draw valid conclusions.

 2 types of sampling techniques are:

1. Probability sampling method

Probability sampling includes a random selection of participants from a large population.  Probability sampling enables you to make statistical assumptions about the entire group. It is the technique by utilizing which you can provide every individual in a population a chance to get selected as a participant in research. Probability sampling enables you to generate a research outcome that represents the complete population.

The probability sampling technique can be categorized into 4 categories these are:

a) Simple random sampling

By utilizing a random sampling technique you can provide all people in the population an opportunity to get selected for research.  It is very much important for you to make sure that the population which you have selected represents the entire population. There are some tools such as a random number generator that you can utilize for applying the simple random sampling method.

 Example: If your are performing research on 1000 workers. In such a case, before applying a random sampling technique you can allot numbers in front of the name of each worker in the list provided by HR of your organization.  You can use the random generator for making selection of 100 workers from 1000 employees.

b) Systematic sampling

This sampling method in research is somewhat similar to a simple random sampling method.  It is a very much easy method to apply. Here you can choose people at regular intervals.

Example:  You need to organise list of all workers in alphabetical order. From the anywhere, you can select the sample participants for your research paper.

  • Note: After the selection of the sample, it is very much essential for you to ensure that there is no hidden pattern in a list.

Example:  In research method sampling technique these team members are listed in order of seniority, there is a risk that your interval might skip over people in junior roles, resulting in a sample that is skewed towards senior employees.

c) Stratified sampling

You can apply such type of sampling technique when your sampling population consists of mixed characteristics.  This sampling technique in research is considered to be appropriate when you intend to many sure that each character you have to represent in the population.

You can categorize the population into subcategories based on their characteristics. Then after that, you can utilize statistical or mathematical techniques for analyzing and computing the number of people who need to be a sample from every subgroup.  Systematic or random sampling techniques users can utilize for making a selection of samples from the subcategorized population.

 Example: There are 600 females and 400 boys in a group. You must ensure that the sample you have chosen is representative of the gender balance. Therefore, the researcher can categorize the population on the basis of gender as a characteristic.

Then, an investigator by applying the random sampling method on every group you can select 30 girls and 20 boys that will provide you representative sample 50 people.

d) Cluster sampling

It is the sampling technique used in research that includes categorizing the population into small groups.  While categorizing the population into small groups you need to ensure that subgroup also consists of similar characteristics.  By utilizing a cluster sampling technique you can make a selection of a complete subgroup as a sample.

Cluster sampling is a suitable method to apply in research that involves a large population.    In case the cluster is also large than in such a situation, you can select an individual from the subgroup as a participant in the research.

But the major drawback of the cluster sampling method is that there are high chances of error and there could be variations in the cluster. You cannot make sure that the sample cluster which you have selected represents the entire population.

 Example:  An institution has locations in 12 different cities around the country. The researcher does not have the time or resources to visit each workplace and collect data. In such a situation you can utilize the random sampling technique can select 3 offices which are basically a cluster.

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2. Non-probability sampling method

It includes the selection of the participants as per connivance.  In this type of technique, researchers set their criteria for gathering information related to the research topic.

In the Sampling technique of the Research methodology section, you need to specify which sampling technique you will use for selecting samples.

In the context of the non-random sampling technique, you need to select participants based on non-random criteria. It is the easiest and simplest technique for selecting participants. But the biggest drawback of this technique is that you cannot make assumptions about the entire population.

The non-probability sampling technique is considered to be more suitable for performing Exploratory and Qualitative research. In both qualitative and exploratory research the main objective of the researcher is to test theories related to the broad population.

In simple words, researchers by performing qualitative and exploratory research intend to develop an understanding of the target population.

The 4 types of non-random sampling techniques are:

a) Convenience Sampling

A convenience sampling is a sampling that involves all those people who are easily accessible to the researcher.

Example: An researcher conducted a survey to obtain information regarding the university’s student support programmes. The researcher asked students to fill a survey form. It is the best and convenient method of collecting information.

But the main drawback of this method of sampling is that you can ensure that the sample is representative of all the students in university.

b) Voluntary response sampling

It is a method of sampling which is somewhat the same as the convenience sampling technique.  Involuntary response sampling, a researcher mainly selects such a sample that they can easily have access to.

In this type of sampling technique, a volunteer is appointed for gathering the information from participants. Sometimes, the investigator also volunteers them (by responding through online surveys).

Example:  An online survey is created by an investigator to collect information from college or university students. By conducting an online survey researcher could gather useful information related to the topic.

Note:  The Main drawback of purposive sampling is that the opinions of a few students represent the view of all other students in college or university.

c) Purposive sampling

It is a method of sampling in which an investigator utilizes their judgment for selecting a sample that is most appropriate for accomplishing research objectives.  The researcher mainly uses purposive sampling for performing Qualitative research.

You can apply purposive sampling in such a type of research where you intend to in-depth knowledge about a particular phenomenon. You need to first set particular criteria and reasons for including a particular sample.

Example:  An investigator conducts a survey to obtain information about kids who have a specific type of handicap. In such type of research, the researcher can purposively make a selection of students with different types of disabilities.

d) Snowball Sampling

If you have difficulty accessing the target population then you can use the snowball sampling technique for selecting participants with the support of other participants.


Example: Researcher performs investigation for gathering information about experience of homeless people in a city. As the investigator does not have easy access to list detail of the homeless therefore the researcher can not apply the probability sampling method.

Investigators by chance meet a homeless person and ask about other homeless people in that particular city.

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It has been summarised from the above article that the selection of an appropriate sampling method is important to draw a valid conclusion. Another fact that has been found is that the size of the population and objective of the research helps in selecting the best sampling technique.

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