Sampling Methods – A Guide with Examples
Published byat August 16th, 2021 , Revised On August 25, 2023
If you are performing research on a large community, organisation, or country, then it may not be possible to collect data individually from each participant. To deal with this issue, you can use a group of a specific number of participants, and this group is referred to as a sample.
The method you apply for selecting your participants is known as the sampling method. It helps in concluding the entire population based on the outcomes of the research.
Uses of Sampling Method
The sampling method is used to:
- Gather data from a large group of population.
- Counter check on data collection.
- Speed up tabulation and publication of results.
- Increase the efficiency of the research.
- Conduct experimental research
- Obtain data for researches on population census.
What is the Difference between Population and Sample?
Before starting with the sampling methods, it is important to understand the difference between sample and population.
It is a group selected from the target population when you aim to study a large population. This group is considered as the representative of the overall targeted population.
If you add the set of individuals with specific characteristics according to the research requirements, the resulting group is called the population.
Sampling Frame Vs. Sampling Size
A list of all the elements from a population is known as the sampling frame.
For instance, you are selecting a telephone directory of students or a list of social media users.
This information can be gathered by contacting any commercial organisation. Sometimes some errors are also possible in the sampling frame due to its discrepancy in selecting samples.
It is considered a subset of the population as it is selected to make the inference to the original population of a study. The chances of accuracy are depended on the size of the population. The larger the size, the more accurate the study is.
When it comes to census, the sample size is the same or parallel with the population size. But to maintain the budget and to consider the time frame, only a representative class is selected.
Methods of Sampling
There are usually two methods of sampling which are used widely. These are considered the best methods:
- Probability Method
- Non-Probability Method
This method of sampling is conducted by using the method of randomisation. In this method, each individual has an equal and independent opportunity to be selected. It has further sub-categories.
- Simple Random Methods
- Stratified Methods
- Systematic Method
- Cluster Method
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Simple Random Method
The participants are selected randomly and assigned to the experimental group. It is known as probability sampling. If the selection is not random, it’s considered non-probability sampling.
Systematic Sampling Method
In this type of sampling, method participants are selected according to the fixed period interval and starting point. The fixed period interval can be calculated by dividing the sample size by the respective population size.
Stratified sampling is a random selection of the participants by dividing them into strata and randomly selecting the participants from each level.
Even though if participants are selected randomly, they can be assigned to the various groups of comparison. Another procedure for selecting the participants is ‘matching.’ The participants are selected from the controlled group to match the experimental groups’ participants in all aspects based on the dependent variables.
It is a kind of sampling where the population is converted into sub-groups called clusters. These sub-groups or clusters are then selected randomly as a sample. The selected group should have all the characteristics of other groups.
Non-probability sampling techniques are often appropriate for exploratory and qualitative research. This type of sample is not to test a hypothesis about a broad population but to develop an initial understanding of a small or under-researched population.
This type of sampling is different from probability, as its criteria are unique. The samples are not selected randomly; rather, these samples are selected according to the researcher’s ability. This might result in a biased result, and participants may find it difficult to be a part of the sample. Still, this is a prevalent method. It has the following types:
- Purposive type sampling
- Referral sampling
- Convenience Sampling
- Quota Sampling
Reading material: Research Prospect has also published a very detailed guide about inductive and deductive reasoning for students.
This type of sampling is based on the aims of the research. Therefore, only such elements of the population will be selected, which are according to the research’s purpose.
This type of sampling is used where the population is not defined or rare. In this technique, one participant is selected according to defined criteria. After that, the same selected participant is asked to refer to other samples fulfilling the study’s criteria. In this way, it goes enlarging its size with the help of the referral.
This type of sampling is applied according to availability. If the samples are not available easily, and the research is getting costly, this technique is applied to select the samples as per convenience.
This type of sampling is done when some standards are already adjusted. In this sampling, the representatives are selected from the population. This selected sample should resemble all the characteristics traits of the population. The size of the sample should reflect the. The participants are selected until sufficient information is gathered.
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Advantages of Sampling Method
Sampling has many advantages, such as:
- It saves a lot of time, as contacting the entire population would be difficult and time-consuming.
- It’s cost-effective.
- It has greater scope and adaptability.
- It provides accurate results.
- It can be managed easily.
Disadvantages of Sampling Method
- It may cause a feeling of discrimination among the participants who are not selected for the study.
- The researcher needs to be skilled, experienced, and qualified to ensure efficient sampling.
- It requires a lot of time, and results may not be reliable.
Frequently Asked Questions
Sampling is the process of selecting a subset of individuals or items from a larger population to gather data. Types include:
- Random Sampling: Each member has an equal chance.
- Stratified Sampling: Divides population into groups for proportional representation.
- Systematic Sampling: Every nth member is chosen.
- Cluster Sampling: Population is divided into clusters; random clusters are selected.
- Convenience Sampling: Convenient individuals are chosen.
- Snowball Sampling: Existing subjects refer new ones.