What is the Purpose of Sampling in Research? Things You Need To Know
Sampling needs additional effort is a general perception of the majority of research students. However, it is one of the most important steps in a research process. It suggests researchers ways to reach the target audience to collect and analyse data for making useful conclusions. In this article, we will discuss the purpose, benefits, and methods of sampling in research.
Sampling in Research:
Sampling is the process that facilitates researchers in managing the data collection process effectively. Simply, it is the process of selecting a subset of a population to collect data from participants. To put it in another way, sampling in research is the process of collecting samples from the target population. Moreover, the sample may be any person, object, and item that seems suitable to give valuable information for solving a scientific query. Samples are some best representatives of a large population that are capable enough to give generalised results.
Purpose Of Sampling In Research:
The main purpose of sampling in research is to draw meaningful conclusions about a population by involving only a few members in the investigation. Researchers need to select samples for a study as it is not at all economical to include all members of a population in a scientific investigation. For example, your research aims to evaluate the knowledge, attitude, and practice of international standards of medical waste management in public sector hospitals in Asian countries.
Obviously, to conduct research on such a broad topic, you have to decide on suitable sampling techniques. This is because; there are approximately 48 countries in Asia, and the collection of data from all public sector hospitals in Asia is indeed time-consuming and expensive. Thereby, sampling will facilitate you to select a few best representatives of Asian public sector hospitals and gather data from them to draw logical inferences.
Benefits of Sampling:
Sampling in research facilitates research in many ways, like:
- It makes data collection easier, especially for broad-spectrum studies.
- Many times some sort of population is very difficult to access; thus, sampling in research is helpful to include them in the study as well. For example, if research aims to address the mental illness of patients with chronic symptoms that are difficult to access then by sampling ,you can draw a conclusion by reaching only a few of them.
- Sampling helps eliminate outliers as much as possible. By selecting an appropriate method of sampling, you can easily collect information from the specific individual ,that may be only extreme patients or patients with moderate symptoms. Thus, it increases the accuracy or reliability of your research results.
Types Of Sampling:
The success of your research depends on how carefully you decide on the samples that are best representative of a whole group or population under study. Basically, there are two types of sampling:
It allows you to select a sample randomly, allowing each member of a population or group to participate in research. Random sampling can be done in four ways:
- Simple Random Sampling: It allows you to select any sample from a population without considering any specific criteria.
- Systematic Sampling: In this sampling, a list of candidates is organised, and samples are selected at regular intervals.
- Stratified Sampling: Subgrouping all potential candidates is the key to stratified sampling.
- Cluster Sampling: It involves making different groups, based on similar characteristics among them, to collect and organise information accordingly.
It is a type of non-random selection of participants based on convenience and other criteria so a researcher can easily collect the desired information. Four potential ways are also suggested to conduct non-probability sampling as well:
- Convenience Sampling: It allows the researcher to include a participant in a study if he/she/it seems most appropriate for a study. It is an easy method of sampling but also has a high risk of associated bias.
- Purposive Sampling: It mostly helps the researchers in qualitative research. It suggests researchers select a sample based on their personal judgment. Usually, inclusion and exclusion criteria help the researcher in making such judgments.
- Snowball Sampling: It is the type of sampling which allows you to use some participants to assess other members of the same group. It is usually used when the researcher does not have all the essential information to reach all potential members of groups, such as unemployed groups.
- Quota Sampling: In this method of sampling, you must collect information from a predefined number of participants by grouping them into sub-groups until you meet your quota requirements.
In doctorate research, you must wisely select the right method of sampling. Remember, it is the sampling technique that helps you reach the target population to draw logical conclusions. Matching your research goals with the goals of a different method of sampling and seeking PhD dissertation help online are two suitable methods to make the right decision about sampling.
All in all, sampling in research helps you in finding the right participants to collect data for a study. It suggests a number of participants sufficient to conduct research based on its scope. However, the most suitable method of sampling for a study depends on the selection of participants ideal to involve in a study.