Sampling fundamentals is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
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Sampling and representativeness
Sampling designs, sample-size logic, weighting and representativeness concepts used to define what a study can and cannot claim.
Cluster overview
Sampling designs, sample-size logic, weighting and representativeness concepts used to define what a study can and cannot claim.
Who is in the target population? Who had a chance to be selected? Which uncertainty comes from sampling and which from coverage or non-response?
Census versus sample is a decision comparison between Census and sample. The useful question is not which is universally better, but which approach fits the objective, evidence, population, timing and consequence of error.
Read the full entry →Target population is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Read the full entry →Sampling frame is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Read the full entry →Sample design is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Read the full entry →Probability sampling uses a known random selection mechanism so each unit has a calculable chance of inclusion. This supports design-based inference when the sampling frame, response process and weighting are appropriately handled.
Read the full entry →Non-probability sampling recruits participants without a known random selection probability. It can be useful for speed, rare audiences or exploratory work, but population inference depends on modelling assumptions and evidence about coverage and selection bias.
Read the full entry →Simple random sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Read the full entry →Systematic sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Read the full entry →Stratified sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Read the full entry →Proportionate stratified sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Read the full entry →Disproportionate stratified sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Read the full entry →Cluster sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Multistage sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Area sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Probability proportional to size is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Household sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Kish grid is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Random route method is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Quota sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Purposive sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Judgment sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Convenience sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Snowball sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Respondent-driven sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Time-location sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Venue-based sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Maximum-variation sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Theoretical sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Expert sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Panel sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
River sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Intercept sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Online-panel sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Sample size determination links the study objective to the required precision, statistical power, design effect, expected variability, subgroup needs and practical constraints. There is no universal sample size that makes a study representative.
Read the full entry →Margin of error is an interval around a sample estimate that reflects uncertainty from probability sampling under stated assumptions. It does not capture coverage error, non-response bias, measurement error or model misspecification.
Read the full entry →Confidence intervals is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Read the full entry →Statistical power is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Read the full entry →Design effect is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Intraclass correlation is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Effective sample size is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Finite population correction is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Oversampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Booster samples is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Rare-population research is a research approach within sampling and representativeness used to reduce uncertainty around who is in the target population? The design should connect the business question, target population, evidence source, analysis and decision rule.
Hard-to-reach populations is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Sample allocation by geography is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Urban-rural sample design is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Longitudinal-panel attrition is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Sample replacement is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Non-response bias is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Coverage error is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Selection bias is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Sampling error versus non-sampling error is a decision comparison between Sampling error and non-sampling error. The useful question is not which is universally better, but which approach fits the objective, evidence, population, timing and consequence of error.
Weighting is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Rim weighting is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Raking is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Iterative proportional fitting is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Post-stratification is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Calibration weighting is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Propensity weighting is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Design weights is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Trimming extreme weights is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Weighting efficiency is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Representative versus balanced samples is a decision comparison between Representative and balanced samples. The useful question is not which is universally better, but which approach fits the objective, evidence, population, timing and consequence of error.
When a sample is not representative is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Sample-quality reporting is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Browse linked entries
Sampling fundamentals
Sampling fundamentals is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryCensus versus sample
Census versus sample is a decision comparison between Census and sample. The useful question is not which is universally better, but which approach fits the objective, evidence, population, timing and consequence of error.
Open entryTarget population
Target population is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entrySampling frame
Sampling frame is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entrySample design
Sample design is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryProbability sampling
Probability sampling uses a known random selection mechanism so each unit has a calculable chance of inclusion. This supports design-based inference when the sampling frame, response process and weighting are appropriately handled.
Open entryNon-probability sampling
Non-probability sampling recruits participants without a known random selection probability. It can be useful for speed, rare audiences or exploratory work, but population inference depends on modelling assumptions and evidence about coverage and selection bias.
Open entrySimple random sampling
Simple random sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entrySystematic sampling
Systematic sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryStratified sampling
Stratified sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryProportionate stratified sampling
Proportionate stratified sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryDisproportionate stratified sampling
Disproportionate stratified sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryCluster sampling
Cluster sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryMultistage sampling
Multistage sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryArea sampling
Area sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryProbability proportional to size
Probability proportional to size is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryHousehold sampling
Household sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryKish grid
Kish grid is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryRandom route method
Random route method is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryQuota sampling
Quota sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryPurposive sampling
Purposive sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryJudgment sampling
Judgment sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryConvenience sampling
Convenience sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entrySnowball sampling
Snowball sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryRespondent-driven sampling
Respondent-driven sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryTime-location sampling
Time-location sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryVenue-based sampling
Venue-based sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryMaximum-variation sampling
Maximum-variation sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryTheoretical sampling
Theoretical sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryExpert sampling
Expert sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryPanel sampling
Panel sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryRiver sampling
River sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryIntercept sampling
Intercept sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryOnline-panel sampling
Online-panel sampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entrySample size determination
Sample size determination links the study objective to the required precision, statistical power, design effect, expected variability, subgroup needs and practical constraints. There is no universal sample size that makes a study representative.
Open entryMargin of error
Margin of error is an interval around a sample estimate that reflects uncertainty from probability sampling under stated assumptions. It does not capture coverage error, non-response bias, measurement error or model misspecification.
Open entryConfidence intervals
Confidence intervals is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryStatistical power
Statistical power is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryDesign effect
Design effect is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryIntraclass correlation
Intraclass correlation is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryEffective sample size
Effective sample size is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryFinite population correction
Finite population correction is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryOversampling
Oversampling is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryBooster samples
Booster samples is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryRare-population research
Rare-population research is a research approach within sampling and representativeness used to reduce uncertainty around who is in the target population? The design should connect the business question, target population, evidence source, analysis and decision rule.
Open entryHard-to-reach populations
Hard-to-reach populations is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryHidden-population research
Hidden-population research is a research approach within sampling and representativeness used to reduce uncertainty around who is in the target population? The design should connect the business question, target population, evidence source, analysis and decision rule.
Open entrySample allocation by geography
Sample allocation by geography is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryUrban-rural sample design
Urban-rural sample design is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryLongitudinal-panel attrition
Longitudinal-panel attrition is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entrySample replacement
Sample replacement is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryNon-response bias
Non-response bias is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryCoverage error
Coverage error is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entrySelection bias
Selection bias is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entrySampling error versus non-sampling error
Sampling error versus non-sampling error is a decision comparison between Sampling error and non-sampling error. The useful question is not which is universally better, but which approach fits the objective, evidence, population, timing and consequence of error.
Open entryWeighting
Weighting is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryRim weighting
Rim weighting is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryRaking
Raking is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryIterative proportional fitting
Iterative proportional fitting is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryPost-stratification
Post-stratification is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryCalibration weighting
Calibration weighting is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryPropensity weighting
Propensity weighting is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryDesign weights
Design weights is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryTrimming extreme weights
Trimming extreme weights is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryWeighting efficiency
Weighting efficiency is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entryRepresentative versus balanced samples
Representative versus balanced samples is a decision comparison between Representative and balanced samples. The useful question is not which is universally better, but which approach fits the objective, evidence, population, timing and consequence of error.
Open entryWhen a sample is not representative
When a sample is not representative is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
Open entrySample-quality reporting
Sample-quality reporting is a concept within sampling and representativeness that helps organise evidence around who is in the target population? It should be defined operationally so different teams measure and interpret it consistently.
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