Sampling

• Goal to select sample that represents that population

• Sampling error: DIfference between the observations in a population and in the sample representing the population

  • Minimize by choosing a representative sample

Sampling Techniques

• Probability sampling

  • Simple random sampling

  • Cluster sampling

  • Stratified sampling

• Non-probability/convenience sampling

  • Volunteer sampling

  • Snowball sampling

  • Quota sampling

Random vs Convenience

• Random sample: All members of the population are equally likely to be chosen

• Research often happens as a convenience sample

  • Participants are not randomly selected, but chosen because they happen to be present for the experiment

Probability

• Simple Random Sample

  • -Individuals are chosen at random from the population such that all members have an equal chance of being selected

• Cluster Sample

  • Identify clusters/groups of individuals (randomly)

  • Individuals are randomly chosen from these clusters/groups

• Stratified Random Sample

  • Subsets of population identified based on demographics

  • Individuals randomly chsoen from the subsets to match the proportion of individuals in sample w/that characteristic in population

• Convenience: Volunteer Samples

  • Individuals are non-randomly chosen from the population such that available individuals are chosen based on who volunteers