Categories of Sampling Techniques

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Categories of Sampling Techniques

• Statistical ( Probability ) Sampling
• Simple Random Sampling
• Stratified Random Sampling
• Cluster Random Sampling
• Systematic Sampling
• Non-Statistical (Non-Probability) Sampling
• Judgment Sampling
• Convenience Sampling

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Simple Random Sampling

• Simple Random Sampling is a method of selecting
  n units out of a population of N such that every
  one of the NCn distinct samples has an equal
  chance of being drawn.
• P(any sample of n from a population of N) is
  equal to the reciprocal of NCn.

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Stratified Random Samples

• In stratified sampling, the population of N
  units is first divided into sub-populations of
  N1, N2, NL units, respectively. These
  sub-populations (strata) are non-overlapping, and
  together comprise the whole of the population, so
  that N1N2NL N When the strata have been
  determined, a sample is drawn from each stratum.
  The sample sizes within the strata are denoted by
  n1, n2, nL

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Cluster Sampling

• Cluster sampling is a method by which the
  population is divided into groups, or clusters,
  and a sample of clusters is taken to represent
  the population. Clusters should be
  representative of the entire population.
• The objective is to form groups of clusters that
  are small images of the target population.

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Systematic Sampling

• For systematic sampling, elements of the
  population are categorized in some way (such as
  alphabetically or numerically) and a random
  starting point is selected. Then every Nth item
  of the categorized population is included until
  the sample size n is satisfied.