Sampling stuff:
Cluster sampling
is a
sampling
technique used when "natural" groupings are evident in a
statistical
population
. It is often used in marketing research. In this technique, the total population is divided into
these groups (or clusters) and a
sample
of the groups is selected. Then the required information is
collected from the elements within each selected group. This may be done for every element in these
groups or a subsample of elements may be selected within each of these groups. The technique works
best when most of the variation in the population is within the groups, not between them.
In
statistics
,
stratified sampling
is a method of
sampling
from a population.
When subpopulations vary considerably, it is advantageous to sample each subpopulation
(stratum) independently.
Stratification
is the process of grouping members of the population
into relatively homogeneous subgroups before sampling. The strata should be mutually
exclusive: every element in the population must be assigned to only one stratum. The strata
should also be collectively exhaustive: no population element can be excluded. Then random or
systematic sampling
is applied within each stratum. This often improves the representativeness
of the sample by reducing sampling error. It can produce a
weighted mean
that has less
variability than the
arithmetic mean
of a
simple random sample
of the population.
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 Fall '08
 MARTIN
 Probability, researcher., 1500m

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