Posted on: 8th Apr 2020 279 Views

Sampling method in Research

The sampling method is a procedure that the researcher performs for selecting a sample from a large population. Ph.D. scholars find selecting a sample as 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 about 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.

Sample in research can be referred to as a group of people whom you have select 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.

NOTE:

  1. It is very crucial for you to define the population considering the research objectives.
  2. In the case population on which you are conducting research is too large then it might difficult for you to have access to sample which represents the entire population.

2. Sampling frame

The sampling frame is a framework that consists of a list of a group from where 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 which 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.

There are 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 select as a participant in research. Probability sampling enables you to generate a research outcome that represents the complete population.

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 select in 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 random number generator which 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 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 as appropriate when you intend to many sure that each character you have to represent in population.

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

 Example: An organisation consists of 600 girls and 400 boys. Here, you need to make sure that the sample which you have selected represents 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 which includes categorizing the population in small groups.  While categorizing the population in 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 which involves a large population.    In case the cluster is also large then in such a situation you can select an individual from subgroup as a participant in 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 organisation has branches in   12 cities across nation.  The researcher does not have the potential to visit each office for collecting information. 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 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.

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 technique are:

a) Convenience Sampling

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

Example: An investigator has performed a survey for gathering information about student support services in the university. 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.   In this type of sampling technique, a volunteer is appointing for gathering the information from participants. Sometimes, the investigator also volunteers them (by responding through online surveys).

Example:  An investigator designs the online survey for gathering the information from students studying in college or university.  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 performs a survey for gathering the information about students suffering from a special kind of disability. 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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Conclusion

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

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