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Non-Probability Sampling

By Jim Frost

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Non-probability sampling refers to sampling methods where not every member of the population has a known or equal chance of being selected. This approach is often faster and cheaper than probability sampling methods but can introduce bias because the sample may not represent the broader population.

Common types of non-probability sampling methods include:

  • Convenience sampling: selecting participants who are easy to reach or readily available.

  • Purposive sampling: selecting participants based on specific characteristics or purpose relevant to the study.

  • Quota sampling: selecting participants to fill predefined categories or quotas (e.g., age, gender) until targets are met.

  • Snowball sampling: recruiting participants through referrals from initial subjects, often used in hard-to-reach populations.

  • Judgmental sampling: relying on the researcher’s expertise to select participants they believe are most useful for the study.

For example, in a study about consumer opinions, researchers might use convenience sampling by surveying only customers who visit a particular store, rather than randomly selecting people from the entire customer base.

Related

Related Articles:
  • Sampling Methods: Different Types in Research
  • Convenience Sampling: Definition & Examples
  • Purposive Sampling: Definition & Examples
  • Quota Sampling: Definition & Examples
  • Snowball Sampling: Definition and Examples
  • Convenience Sampling: Definition & Examples
  • Sampling Methods: Different Types in Research
  • Snowball Sampling: Definition and Example
  • Sampling Bias: Definition & Examples
  • Undercoverage Bias: Definition & Examples
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