Cluster Sampling Definition Examples When To Use

Cluster Sampling Definition

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Explanation

This type of sampling is used in statistics by choosing random samples among the population. Under this method, the researchers focus only on a few samples instead of choosing all subjects from the population. The researchers also opt for the entire cluster and not the subset of the cluster. The most famous cluster used in statistics is the geographical cluster.

Examples of Cluster Sampling

There are many examples as if a researcher opts to conduct a study to review the presentation of the sophomore in business culture in the US, so it is impossible to involve sophomores to organize research in every university in the US. Using this sampling method, researchers can easily club all the universities in the US, with each city diversifying into one cluster. These clusters specify all the sophomore strengths of students in the country. The next step is picking up clusters for the study or research. However, by using systematic samplingSystematic SamplingSystematic sampling is a method of selecting various elements ordered from a sampling frame. This statistical procedure begins with a random selection of elements from a list, and then selects each sampling interval from the frame.read more or simple sampling, one can pick each selected cluster for sophomores of every University for successful research. This method is done on a sample that contains multiple parameters like background, habits, demographics, or other attributes, which are the core of research. This technique will justify that instead of selecting the whole population data, select only the bifurcated data for more effectiveness.

Another example is where an organization is surveying the performance of smartphones in Germany. They can diversify the whole population into clusters and then select the cities with the highest population. So that researchers filter the ones using mobile phones. This multiple sampling is called cluster sampling.

Types

There are three types which are as follows:

Single-Stage: In this sampling stage, one will do it only once. They selected random samples only once at a time. For instance, an NGO wants to sample girls across six neighboring cities to grant education. They chose a random sample of selected towns of girls who were deprived of education.Two-Stage: This stage of a cluster is better than a single-stage cluster as it shows more reliable results. Under this method, more filters are preferred, which gives improved results. Instead of choosing the entire cluster, it will work over the handful of clusters necessary for the sampling through simple or systematic random sampling.Multiple Stage: This method is a kind of complicated one as compared to other stages. For multiple geographies, research should be more complex, and it has been done through multiple stage clusters technique of sampling.

Requirements

These sampling elements should be heterogeneous. The population’s research should enclose a distinct subpopulation of altered types.Every cluster should be created as a representation of the whole population of the sample.Every cluster should be arranged in a mutually exclusiveMutually ExclusiveMutually exclusive refers to those statistical events which cannot take place at the same time. Thus, these events are entirely independent of one another, i.e., one event’s outcome has no impact on the other event’s result.read more nature so that it would not be possible for the cluster to occur simultaneously.

When to use Cluster Sampling?

Cluster sampling is used by researchers in statistics when natural groups are there in the population. The entire population divides into clusters in such a way as to create random sampling. It is typically used in market research where the researcher cannot get information regarding the entire population. On the contrary, they can get information regarding clusters.

Applications

This sampling method is used in geographical and market research at large. Research on geographical clusters is expensive as compared to other areas of research. The number of samples increases in this case for more accuracy. This method is also cost-effective for researchers. This technique one may use in scenarios like natural calamities and wars. The application of this method is on a large scale while implementing it by researchers.

Advantages

Requires fewer resources: This method is the most effective as it requires fewer resources to research as there is a selection of certain clusters out of the entire population. Hence, it is cheaper than other sampling methods and is also considered cost-effective.More Feasible: This technique is more feasible in terms of complexity, as it is very helpful in geographical research.

Disadvantages

Biased Samples: This sampling is very biased as clusters are randomly selected from the entire population. It has also formed a biased opinion regarding research.High Sampling ErrorSampling ErrorThe sampling error formula is used to calculate statistical error that occurs when the person conducting the test doesn’t select a sample that represents the whole population under consideration. Formula for sampling error = Z x (σ /√n)read more: The samples are generally error-based compared to another simple sampling method.

Conclusion

Cluster sampling is the method used by researchers for geographical data and market research. The population is subdivided into different clusters to select the sample randomly. It is a very helpful technique for researchers. It has many advantages and disadvantages but is commonly used in statistics for different projects. Moreover, this method of sampling is reliable and affordable for the researchers.