we employ cluster analysis to derive the clusters representing different dimensions of the profile of the respondets on the set of variables. in this sense, each cluster is a unique representation of the population.
in sampling, we discuss cluster sampling also. in cluster sampling, cluster is understood as the unit of population and we can select some clusters randomly or otherwise.
I think the meaning of cluster in cluster sampling and cluster analysis seems to be paradoxical.
please clarify my doubt.
Please let me know if these references/sites are useful to you:
[1. Cluster Sampling
ocw.jhsph.edu/courses/StatMethodsForSampleSurveys/PDFs/Lecture5.pdfCached
The households are “Secondary Sampling Units” (SSU). Definition: In cluster sampling, cluster, i.e., a group of population elements, constitutes the sampling unit ...
2. 9 Cluster Sampling Area sampling Examples - IITK
home.iitk.ac.in/~shalab/sampling/chapter9-sampling-cluster-sampling.pdfCached
In both the examples, draw a sample of clusters from houses/villages and then collect the .... is the mean sum of squares between cluster means in the sample .
3. Cluster Sampling
halweb.uc3m.es/esp/Personal/personas/jmmarin/esp/MetQ/Talk4.pdfCached
A cluster sample is a probability sample in which each sampling unit is a collection or ... The estimator of the population mean µ is the sample mean ¯y, given by.
4. Sampling Theory CLUSTER SAMPLING - nptel
nptel.ac.in/courses/111104073/Module9/Lecture30.pdfCached
In cluster sampling. ▫ divide the whole population into clusters according to some well defined rule. ▫ Treat the clusters as sampling units. ▫ Choose a sample of ...
5. Notes on Cluster Sampling for Statistics 36-303 ... - CMU Statistics
www.stat.cmu.edu/~fienberg/Stat36-303-03/clustering-rev03.pdfCached
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Mar 18, 2003 - sample. In cluster sampling, we divide the population up into clusters, and ... for the variance of an estimate for a proportion or for a mean from.
Dennis
Dennis Mazur
thank you prof. Dennis Mazur
i will go through those reference and inform you whether they are really useful to me or not.
And for the simple English response:
Cluster sampling means that you, the researcher, already know what the groups or "clusters" are in your potential population, and you have made a deliberate decision to sample in a way to make use of your knowledge of those groups by sampling them specifically.
Cluster analysis means that you, the researcher, do not know if there are specific groups or "clusters" in your sample and are using empirical methods to use the data you have collected on that sample to tell you if there are groups (and what those groups might be).
Differences:
- In cluster sampling, your knowledge informs who you gather data from. The sample you end up with has groups already defined.
- In cluster analysis, you already have gathered data from your sample (based on whatever sampling parameters you used) and are now using that information to tell you what groups there are.
You can, in fact, do both - employ cluster sampling to gather data, then use the data from your clustered sample to test whether there are other groups you did not know about, or whether the groups you deliberately targeted in fact behave as a group relative to the data you collected.
Cluster sampling is a sampling technique whereby the population is partitioned into clusters and clusters are the sampling units. That is, only some clusters are chosen into the sample. Cluster analysis on the other hand is a multivariate statistical analysis whereby a set of variables are grouped into a comparatively fewer clusters. Often this is by the use of a denodogram. Cluster sampling and cluster analysis are therefore not related techniques.
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