Sampling Method in Research – Definition & Types Explained

02/11/2020 | George Orwell | 495

What is Sampling?

Sampling  is basically a statistical analysis technique that you can apply for selecting the predetermined number of a sample from a large population having similar characteristics. When you perform the investigation, due to lack of resources and time you would not able to gather information from each and every one, in such case you can use sampling method for selecting participants.

Besides gathering facts from all people individually you can select the sample. Researcher use the term sample is  for a group of people which they have select as participants in research. Sampling is the procedure that you can use for selecting a few people from a large population as participants in research.

What are different sampling method?

The sampling method can be categorized into two these are:

  • Probability: It is a type of sampling method in which  you need to select participants a randomly. The probability sampling method enables you to make a statistical assumption about the population.
  • Non-probability: It involves such a type of research where you cannot give the population a chance to get selected as participants in the research.

Uses of both probability and non-probability sampling method

  • Probability sampling: You can use a probability sampling method in case when you want to generate an outcome that represents the entire population.
  • Non probability sampling: It is the type of sampling method which is most suitable for performing both qualitative and exploratory investigation. Non-probability sampling technique will enable you to gain knowledge about the under-researched population.

Methods Of Sampling

Types of probability sampling method

The different types of probability sampling methods are:

1.Simple random sampling:

It is a type of probability sampling method by using which you can provide all people in the population with a chance to get select as a participant in the research process. While applying this method you need to make sure that the sampling structure which has been chosen covers the entire population.

For example: You for conducting the investigation are planning to select 100 employees out of a thousand workers in a company. You can give all thousand employee number and by using the random sampling technique can select 100 workers.

2. Systematic sampling:

It is a probability sampling method that includes a listing of all people. In a systematic sampling technique, all people are chosen at a regular interval of time.

For example: If you want to choose a sample of 100 people out of 1000 employees you can arrange or list them in an alphabetical way. Then from the list of 1000 employees, you can chose every sixth or twelfths person as participant in research. Then afterward you can select every fifth person and in this way, you can make the selection of all 100 people.

While making the application of systematic sampling you need to confirm that there is no hidden pattern. For example, if you arrange database in alphabetical order you aware of that while performing the sampling.

3. Stratified sampling:

You can apply the stratified sampling method where the population involves mixed characteristics and you want to make sure that you have represent  each character is equally . In this sampling method,researcher characterize the entire population on the basis of different characteristics such as on the basis of demographics, job role, etc.

For example : An organization consisting of 500 female and 100 male workers. While selecting a sample you want to make sure that the sample demonstrates gender balance then you can categorize the entire population on the basis of gender. Then after that, you can apply a random sampling technique to every group. After that, you need to select 80 women and 20 men.

4. Cluster sampling:

it is a type of sampling technique that mainly includes categorizing the population into subgroups. While applying this technique you need to make sure that every group consists of similar characteristics. The cluster sampling method is suitable when you have to select a sample from a large population. The biggest disadvantage of this method is that there are high chances of error in the selection of samples. Another major drawback of this method is that you can’t make sure those samples that you have selected using a cluster sampling technique represent the whole population.

For example: you want to conduct the investigation in order to analyze whether employees working in an organization are satisfied with the working environment. Companies where you want to perform surveys consist of 1000 employees.

king fisher airlines has 12 branches located in different cities. In such a case, you can not reach each and every employee for collecting information; therefore you can select 5 offices randomly. Which is basically is  your clusters?

Types of non-Probability sampling method

In non-probability sampling,researcher need to use  a non-randomized criterion for selecting the sample. The different types of non-probability sampling method are:

1.Convinces sampling:

in this type of sampling technique, researcher selects those participants who are easily accessible by an investigator. One of the biggest advantages is that it is less expensive and you can collect information easily. The major drawback of the method is that you can’t make sure that people  whom you have select as participants represent the entire population.

2.Voluntary response sampling:

It is somewhat like a convenient sampling method. The voluntary sampling technique mainly involves selecting participants and directly approaching them. One biggest drawback of this method is that there are high chances of biasness.

For Example: Suppose you by performing the investigation and collecting information about student support services. You could share the survey questionnaire with all the students at the university. But while applying this technique you will not able to confirm that the response provides with few students represents the perspective of other students.

3. Purposive sampling Method

You, in order to apply the purposive sampling method, will require utilizing your personal judgment for selecting the sample. Such type of sampling technique researcher mainly utilize for performing  Qualitative research. You can also utilize it when you intend to develop a in depth understanding of a particular situation. You need to set proper criteria and reason for inclusion in order to make purposive sampling effective.

For example: you want to perform an investigation for analyzing the academic performance of people suffering from a special type of disability. You can purposefully select disabled people for collecting a huge amount of information about their academic performance.

4.Snowball sampling:

You can utilize this sampling technique for selecting few people as participants with the support of other people.

For example: You are trying to gather information about homeliness people  but you don’t have access to the list . Suddenly you  met a person who gets ready to act as a participant in investigation.  You can ask him to provide contact detail of other people.

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