Sampling Methods
Sampling Methods
| Method | How it works | Main limitation |
|---|---|---|
| Simple random | Select from a complete population list so every possible sample of the fixed size has the same chance of selection. | An incomplete list excludes part of the population. |
| Systematic | Choose a random start, then every \(k\)th individual. | A repeating pattern in the list can bias selection. |
| Stratified | Divide into relevant groups, then randomly sample within every group. | Requires group membership and suitable group sizes. |
| Quota | Recruit until specified group totals are met. | Selection within each group is not necessarily random. |
| Convenience | Use individuals easiest to reach. | Easy access need not represent the population. |
Example: a school has \(360\) younger and \(240\) older students. A proportional stratified sample of \(50\) selects \(30\) and \(20\) respectively, randomly within each group.
Describe a sampling method as an executable procedure: identify the population list, the selection rule and the sample size. For systematic sampling, choose the starting position randomly before taking every kth member. Do not select the first member simply because the list starts there.
Stratified and quota samples can have the same group totals but different selection mechanisms. Random selection within each stratum distinguishes a stratified design. In a convenience sample, inviting nearby volunteers also introduces self-selection: willing respondents may differ from those who do not respond.
Assess a proposed method against the purpose of the study. Check who is absent from the sampling frame, whether non-response is related to the measured variable, and whether the list has a repeating pattern. A larger sample reduces random variation but cannot repair a systematically unrepresentative selection rule.
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