IT IS A AMOUNT OF SOME THING . CLUSTER OF STARS
In a cluster sample, researchers divide subjects into strata (like cities, for example), randomly select a few strata (draw the names of a few cities from a hat) and sample every subject in those strata (question everyone in that city.) A significant disadvantage is that you may select strata that completely overlook a feature relevant to your study.
Advantages of cluster sampling include that it's inexpensive, fast, and simple. A disadvantage is that it is known to have a high sampling error.
Cluster sampling is a scheme which is used when sampling from the whole population would be too expensive - in terms of time or money. The sample space is divided into clusters, a random sample of clusters is selected and then every member of the population within the selected clusters is studied.For example, suppose you wanted to collect information from schools across a country and had calculated that a 5% sample was required. Rather than criss-crossing the country, you could divide the country into units: for example counties. You then select counties (your clusters) so that they cover 5% of the nation's schools. Visit each chosen county and sample all schools in it. The selection of counties would probably also need to be controlled so that urban and rural areas are properly represented.
Cluster Sampling
It is called one-stage cluster sampling. If random samples are taken within the selected clusters then it is two-stage cluster sampling.
In a cluster sample, researchers divide subjects into strata (like cities, for example), randomly select a few strata (draw the names of a few cities from a hat) and sample every subject in those strata (question everyone in that city.) A significant disadvantage is that you may select strata that completely overlook a feature relevant to your study.
There are circumstances when it is important and others when it is not. If, for example, you wanted a sample of all schools in the country, it would make more sense to go for cluster sampling. A lot of market research work will require quota sampling. So the supremacy of a random sample is a myth.
Advantages of cluster sampling include that it's inexpensive, fast, and simple. A disadvantage is that it is known to have a high sampling error.
Cluster sampling is a scheme which is used when sampling from the whole population would be too expensive - in terms of time or money. The sample space is divided into clusters, a random sample of clusters is selected and then every member of the population within the selected clusters is studied.For example, suppose you wanted to collect information from schools across a country and had calculated that a 5% sample was required. Rather than criss-crossing the country, you could divide the country into units: for example counties. You then select counties (your clusters) so that they cover 5% of the nation's schools. Visit each chosen county and sample all schools in it. The selection of counties would probably also need to be controlled so that urban and rural areas are properly represented.
Simple random sampling.
Cluster Sampling
a example of a hendecagon is a hedecagon
sample example
No, a typical soil sample is heterogeneous.
When discussing race, you can use "cluster" to refer to the grouping of individuals with similar racial characteristics. For example, "In this diverse city, neighborhoods often cluster by race, creating pockets of different ethnic communities."
example of antithesis?
Sample, example.