difference between stratified random sampling and cluster sampling
Cluster 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 strata. In stratified sampling, a random sample is drawn from each of the strata, whereas in cluster sampling only the selected clusters are sampled. A common motivation of cluster sampling is to reduce costs by increasing sampling efficiency. This contrasts with stratified sampling where the motivation is to increase precision.
p-chart The binomial distribution is the basis for the p-chart and requires the following assumptions:[2]:267
Limit of a function (the Dirichlet function) has no limit at any x-coordinate.
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