Understanding Ways to Collect Data (7)

Sampling in Qualitative and Quantitative Research

Sampling in Qualitative and Quantitative Research

1. General Considerations for Sample Size in Qualitative Research

  • No strict rules: Sample size in qualitative research depends on the research purpose and the amount of data needed (Roller & Lavrakas, 2015).
  • Justification required: Researchers must provide a rationale for their sample size.
  • Variation in sample size:
    • A single case may suffice for projects like oral history or autoethnography.
    • 20+ participants may be needed for focus group studies.
  • Guidelines for interviews:
    • No rigid rules; sample size should be planned upfront.
    • Kvale & Brinkmann (2008): "Interview as many subjects as necessary to find out what you need to know."

2. Sampling Strategies

All sampling methods fall under two broad categories: Probability Sampling and Non-Probability Sampling.

A. Probability Sampling

  • Simple Random Sampling (SRS): Every element has an equal chance of selection.
  • Systematic Random Sampling: First element is randomly selected, then every k-th element is chosen.
  • Cluster Sampling: Uses pre-existing clusters (e.g., universities) and involves a two-stage selection process.
  • Stratified Random Sampling: Population divided into strata based on shared characteristics.

B. Non-Probability Sampling

  • Purposeful Sampling (Purposive/Judgment Sampling): Focuses on "information-rich cases."
  • Snowball Sampling (Chain Sampling): One participant leads to another.
  • Exemplar of the Phenomenon of Interest: Selection of a single significant case providing rich data.
  • Homogeneous Sampling: Participants share a common characteristic.
  • Accidental Sampling: Selection based on convenience.
  • Quota Sampling: Ensures representation of diverse elements in the population.

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