The main difference between cluster sampling and stratified sampling is that in cluster sampling the cluster is treated as the sampling unit so analysis is done on a population of clusters ( at least in the first stage ).
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Cluster sampling ( also known as clustered sampling ) generally increases the variability of sample estimates above that of simple random sampling, depending on how the clusters differ between one another as compared to the within-cluster variation.
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To search for clusters in the optical data, one technique DES will use is known as red sequence optical cluster finding This well-known technique has been applied to smaller cluster samples from the SDSS and the RCS-II cluster surveys.
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Because of the impracticality of carrying out an evenly distributed survey, particularly during a war, Roberts'surveys use " cluster sampling ", dividing the area into a number of randomly selected, approximately equally populated regions; a random point is chosen within each region, and a fixed number of the households closest to that point are surveyed as a " cluster ".
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Expert investigation of this question shows results that " strongly suggest that the extensive reporting of na�ve chi-square independence tests using cross-cultural data sets over the past several decades has led to incorrect rejection of null hypotheses at levels much higher than the expected 5 % rate . " The investigator concludes that " Incorrect theories that have been'saved'by na�ve chi-square tests with comparative data may yet be more rigorously tested another day . " Once again, the adjusted variance of a cluster sample is given as one multiplied by 1 + " d " ( " k " + 1 ) where " k " is the average size of a cluster, and a more complicated correction is given for the variance of contingency table correlations with " r " rows and " c " columns.
