What Is Cluster Sampling ?
Cluster sampling is a type of sampling method where researchers divide the population into different groups or clusters to gather data and information. Clusters should be internally heterogeneous and externally homogeneous. By using this technique, large data samples can be created by consuming less resources and costs. It is more feasible to collect data and information than other sampling methods.
Benefits Or Advantages Of Cluster Sampling
The main advantages of cluster sampling method can be highlighted as follows:
1. It Consumes Less Time, Cost And Effort
The main benefit of cluster sampling is that it requires less time and effort
than other methods of sampling. It consumes fewer resources (limited number of
clusters), and fewer costs ( travelling expenses, listing expenses
,administrative expenses etc.). It can be conducted quickly in less time than
random and stratified sampling.
2. Suitability
This sampling is suitable for large population and wider geographical area
because sample size can be increased as per the requirement. It is applicable
for market research and to collect data and information from different
institutions.
3. Most Feasible Method Of Sampling
Another advantage of cluster sampling is that it is more feasible than random sampling because each and every individual
within a cluster represents the entire population because the population is
carefully divided into homogeneous groups.
4. Larger Data
Cluster sampling provides large data to the researcher because of large
population group.
5. Easy Implementation Of Data
Data and information collected from cluster sampling can be implemented easily
and quickly.
3. Possibility Of Sampling Error
Drawbacks Or Disadvantages Of Cluster Sampling
The main disadvantages of cluster sampling can be highlighted as follows:
1. Complex Method
It is more complicated than random sampling because it requires proper plan
and attention to choose clusters from large population.
2. Less Accuracy
It may lack statistical accuracy in case of biased samples,
over-representation or under-representation of data, and carelessness of the
researcher.
Also Read:
Limited clusters are selected from very large population and from wider
geographical area. It increases the chance of high sampling error.
4. Not Suitable
It is not suitable for small group of population. Another disadvantage of this method is that findings obtained from one population does not apply on other
similar groups from other population.
Pros And Cons Of Cluster Sampling In Short
Pros:
- It consumes fewer resources such as time, expenses and effort
- This method is more feasible than other sampling approaches
- It is appropriate for large population group and wider geographical area
- Large data sample can be obtained
Cons:
- There is a high chance of sampling error
- It is complex than other sampling methods
- It is not appropriate in case of small population
- It may lack accuracy
