Difference Wiki

Stratified Sampling vs. Cluster Sampling: What's the Difference?

Edited by Sawaira Riaz || By Sumera Saeed || Updated on October 19, 2023
Stratified sampling divides a population into subgroups and samples from each, while cluster sampling divides the population into clusters, sampling entire clusters.

Key Differences

Stratified sampling and cluster sampling are both probability sampling techniques used in research to select representative samples from larger populations. While stratified sampling breaks down the population into homogenous subgroups (or strata) and draws samples from each subgroup, cluster sampling divides the population into heterogeneous clusters and then randomly selects a few clusters to be surveyed in their entirety.
Sumera Saeed
Oct 19, 2023
In stratified sampling, the aim is to ensure that each subgroup (stratum) of the population is adequately represented within the sample. For instance, if researching gender differences, a researcher might use stratified sampling to ensure both male and female perspectives are represented equally. On the other hand, cluster sampling is more about convenience and efficiency. A researcher might use cluster sampling when it's too costly or challenging to study the population widely, opting instead to thoroughly study a few clusters.
Sumera Saeed
Oct 19, 2023
Stratified sampling requires that the researcher knows the key characteristics of the population to divide it into relevant strata. For example, if studying income levels, the population might be divided into low, middle, and high-income strata. Conversely, with cluster sampling, there's no need to know the individual characteristics of the population members. The division is more spatial or based on certain logistical parameters, like city blocks or schools.
Sumera Saeed
Oct 19, 2023
While stratified sampling ensures that each subgroup is represented proportionally in the sample, which can lead to increased accuracy and reduced sampling error, cluster sampling can sometimes introduce more sampling error. This is because the selected clusters might not be entirely representative of the entire population.
Sumera Saeed
Oct 19, 2023
Cost and feasibility often play a role in choosing between stratified sampling and cluster sampling. While stratified sampling might provide more precision, it can sometimes be more expensive or time-consuming than cluster sampling, which offers more logistical convenience, especially when dealing with large geographic areas or dispersed populations.
Sara Rehman
Oct 19, 2023
ADVERTISEMENT

Comparison Chart

Definition

Divides population into homogenous subgroups.
Divides population into heterogeneous clusters.
Sumera Saeed
Oct 19, 2023

Representation

Ensures representation from each subgroup.
Studies entire clusters without individual representation.
Sumera Saeed
Oct 19, 2023

Knowledge of Population

Requires knowledge of population characteristics.
Doesn't require knowledge of individual characteristics.
Sumera Saeed
Oct 19, 2023

Sampling Error

Typically has reduced sampling error.
Might introduce more sampling error.
Harlon Moss
Oct 19, 2023

Cost & Feasibility

Can be more precise but potentially more costly.
Can be more logistically convenient and cost-effective.
Janet White
Oct 19, 2023
ADVERTISEMENT

Stratified Sampling and Cluster Sampling Definitions

Stratified Sampling

Reduces sampling bias by proportionate selection.
Stratified sampling was chosen to minimize bias in the gender study.
Sumera Saeed
Oct 19, 2023

Cluster Sampling

Surveys entire clusters rather than individuals.
Through cluster sampling, three entire schools were surveyed rather than picking individual students.
Sumera Saeed
Oct 19, 2023

Stratified Sampling

Ensures each subgroup's representation in the sample.
Stratified sampling ensured equal representation of both urban and rural perspectives.
Sawaira Riaz
Oct 19, 2023

Cluster Sampling

Doesn't require detailed population characteristics knowledge.
Using cluster sampling, they surveyed entire neighborhoods without needing demographics.
Harlon Moss
Oct 19, 2023

Stratified Sampling

Enhances precision in certain research contexts.
To gain a clearer picture of regional preferences, they opted for stratified sampling.
Janet White
Oct 19, 2023

Cluster Sampling

A method dividing the population into clusters.
Given the country's vastness, the survey used cluster sampling by province.
Sawaira Riaz
Oct 19, 2023

Stratified Sampling

Requires knowledge of population characteristics.
Using stratified sampling, the team divided participants based on age groups.
Janet White
Oct 19, 2023

Cluster Sampling

Often used for logistical convenience.
Cluster sampling was ideal for the study as it reduced travel costs.
Sumera Saeed
Oct 19, 2023

Stratified Sampling

A method dividing a population into subgroups.
To study income differences, the researcher used stratified sampling based on income brackets.
Sumera Saeed
Oct 19, 2023

Cluster Sampling

Can introduce more sampling error.
While efficient, their cluster sampling approach raised concerns about representativeness.
Sumera Saeed
Oct 19, 2023

FAQs

How do I ensure the clusters in cluster sampling are diverse?

Random selection of clusters can help ensure diversity and representativeness.
Sumera Saeed
Oct 19, 2023

Which sampling method ensures proportional representation?

Stratified sampling ensures proportional representation from each subgroup.
Sumera Saeed
Oct 19, 2023

Is cluster sampling more convenient in large geographic studies?

Yes, cluster sampling is often chosen for its logistical convenience in large geographic areas.
Sawaira Riaz
Oct 19, 2023

Can stratified sampling be more costly than cluster sampling?

Yes, stratified sampling can sometimes be more expensive due to its precision and need for detailed population knowledge.
Sumera Saeed
Oct 19, 2023

Which method is best for studying specific subgroups in detail?

Stratified sampling is better for detailed study of specific subgroups.
Sumera Saeed
Oct 19, 2023

How is the sample size determined in cluster sampling?

It depends on the number of clusters chosen and the size of each cluster.
Sumera Saeed
Oct 19, 2023

Does stratified sampling require knowledge of the population's characteristics?

Yes, stratified sampling requires knowledge of the population's key characteristics to divide it into relevant strata.
Sumera Saeed
Oct 19, 2023

Can I combine both sampling methods in one study?

Yes, a combination known as multistage sampling can utilize both methods.
Janet White
Oct 19, 2023

Is cluster sampling always based on geography?

No, while often based on spatial divisions, clusters can be any group, such as schools or companies.
Sara Rehman
Oct 19, 2023

Does stratified sampling involve studying every member of a subgroup?

No, only a random sample from each subgroup is studied in stratified sampling.
Janet White
Oct 19, 2023

Why is stratified sampling considered more precise?

Because it ensures each subgroup's proportional representation, reducing sampling bias.
Harlon Moss
Oct 19, 2023

What are the strata in stratified sampling based on?

Strata can be based on characteristics like age, gender, income, or any relevant categorical variable.
Aimie Carlson
Oct 19, 2023

Are strata in stratified sampling heterogeneous or homogenous?

Strata in stratified sampling are homogenous, meaning members within a stratum share similar characteristics.
Sumera Saeed
Oct 19, 2023

Does stratified sampling work well with small populations?

It can, but there needs to be clear and meaningful stratification even in smaller populations.
Sumera Saeed
Oct 19, 2023

What's the main advantage of stratified sampling over cluster sampling?

Stratified sampling ensures proportional representation, enhancing precision and reducing bias.
Harlon Moss
Oct 19, 2023

Which method is more prone to sampling error?

Cluster sampling can sometimes introduce more sampling error compared to stratified sampling.
Janet White
Oct 19, 2023

Can cluster sampling be used when the population's characteristics are unknown?

Yes, cluster sampling doesn't require detailed knowledge of individual population characteristics.
Sumera Saeed
Oct 19, 2023

How many clusters should I choose in cluster sampling?

It varies based on the study's objective, resources, and desired precision.
Sumera Saeed
Oct 19, 2023

Can the choice of clusters in cluster sampling introduce bias?

Yes, if clusters chosen aren't representative of the population, it can introduce bias.
Sumera Saeed
Oct 19, 2023

In cluster sampling, do all clusters need to be of the same size?

No, clusters in cluster sampling can vary in size.
Sumera Saeed
Oct 19, 2023
About Author
Written by
Sumera Saeed
Sumera is an experienced content writer and editor with a niche in comparative analysis. At Diffeence Wiki, she crafts clear and unbiased comparisons to guide readers in making informed decisions. With a dedication to thorough research and quality, Sumera's work stands out in the digital realm. Off the clock, she enjoys reading and exploring diverse cultures.
Edited by
Sawaira Riaz
Sawaira is a dedicated content editor at difference.wiki, where she meticulously refines articles to ensure clarity and accuracy. With a keen eye for detail, she upholds the site's commitment to delivering insightful and precise content.

Trending Comparisons

Popular Comparisons

New Comparisons