Statistics: Sampling Methods

Identifying the Best Method to Create a Sample

As discussed in Population versus Sample, sampling provides a more cost and time-effective means of mining data versus attempting to gather an entire population.
Building the sample requires deciding which sampling methods best suites your statistical needs:

  • Simple Random Sampling: This represents the best method as it provides every member of the population has equal chance being selected for sample, but is rarely used due to the inability to conduct a truly random sample because of subjectivity inherit within the person conducting the study – their preferences prevent them from being truly objective.
  • Stratified Sampling: The population is split into non-overlapping groups from which random sampling is executed. For example, this method might produce groups of medical patients according to their age group.
    Systematic Sampling: This is systematic in that every nth individual from the population is selected for the sample.
  • Convenience Sampling: This method allows participants to volunteer, which might not be advantageous because of characteristics inherit in those who volunteer versus those that might – those characteristics may not be evaluated as part of the study’s results.

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