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Can cluster sampling be combined with stratified sampling?
Cluster sampling can be combined with stratified sampling, because a population can be divided in L strata and a cluster sample can be selected from each stratum. As in the case of ratio estimators we can consider separate estimators and combined estimators.
What is cluster sampling and stratified sampling?
In Stratified Sampling, elements within each stratum are sampled. In Cluster Sampling, only selected clusters are sampled. In Stratified Sampling, from each stratum, a random sample is selected.
Is stratified sampling a cluster sample?
In stratified sampling, a sample is drawn from each strata (using a random sampling method like simple random sampling or systematic sampling). In cluster sampling, the sampling unit is the whole cluster; Instead of sampling individuals from within each group, a researcher will study whole clusters.
What is a stratified cluster sample?
Stratified Sampling Definition. Members of this sample are chosen from naturally divided groups called clusters, by randomly selecting elements to be a part of the sample. Members of this sample are randomly chosen from non-overlapping, homogeneous strata. Purpose. Cost reduction and increased efficiency.
What is the main difference between cluster and stratified sampling?
The main difference between cluster sampling and stratified sampling is that in cluster sampling the cluster is treated as the sampling unit so sampling is done on a population of clusters (at least in the first stage). In stratified sampling, the sampling is done on elements within each stratum.
What’s the difference between quota and stratified sample?
The main difference between stratified sampling and quota sampling is that stratified sampling would select the students using a probability sampling method such as simple random sampling or systematic sampling. In quota sampling, no such technique is used.
What are the advantages of stratified sampling?
Stratified Random Sampling provides better precision as it takes the samples proportional to the random population.
What is an example of stratified sampling?
A real-world example of using stratified sampling would be for a political survey. If the respondents needed to reflect the diversity of the population, the researcher would specifically seek to include participants of various minority groups such as race or religion, based on their proportionality to…
What is cluster sample method?
Cluster Sampling. Cluster random sampling is a sampling method in which the population is first divided into clusters (A cluster is a heterogeneous subset of the population). Then a simple random sample of clusters is taken. All the members of the selected clusters together constitute the sample.
What is an example of cluster sampling?
An example of cluster sampling is area sampling or geographical cluster sampling. Each cluster is a geographical area. Because a geographically dispersed population can be expensive to survey, greater economy than simple random sampling can be achieved by grouping several respondents within a local area into a cluster.