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Probability Sampling

👥 Sociology By CampusDown Wiki Editorial Team Last updated
Quick answer: Probability sampling selects elements randomly with known probabilities—simple random, systematic, stratified or cluster—so sampling error can be estimated and results generalised.
Contents
  1. 1. Key terms
  2. 2. Types
  3. 3. Sampling and non-sampling error
  4. 4. References

Key terms

The population is the full target group, the sampling frame is the list from which elements are drawn, and the sample is the selected subset; frame mismatch causes coverage error.

Types

  • Simple random: equal chance via random numbers.
  • Systematic: random start then every k-th element (k = N/n); periodicity in the list can bias it.
  • Stratified: random selection within strata; disproportionate designs need weights.
  • Cluster: random selection of groups such as schools; multistage designs are used in national household surveys.

Sampling and non-sampling error

Sampling error shrinks with larger samples and is reported as a margin of error or confidence interval; non-response, measurement and frame errors do not. When probability methods are impractical, researchers use non-probability sampling.

References

  1. Kish, L. (1965). Survey Sampling. Wiley.
  2. Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley.
  3. Babbie, E. (2021). The Practice of Social Research (15th ed.). Cengage.
  4. Groves, R. M., et al. (2009). Survey Methodology (2nd ed.). Wiley.

Reports and materials that use this theory (Korean)

There are no materials dedicated to this theory yet, but you can search related reports in the CampusDown library (Korean).

Find more reports · Search '확률표집' on CampusDown →
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This article was last updated on October 15, 2026. It is based on widely recognized original works and textbooks; when citing it in a paper, please check the original sources listed in the references.