Population and Sampling Methods

Population

• Defined as the group to which study results apply (target group).

Non-Probability Sampling (no random selection)

• Key feature: individuals do not have equal selection chance.
• Types:
  • Convenience (reliance on available subjects)
  • Purposive (select pre-defined group)
  • Snowball (participants recruit others; useful for hard-to-reach groups)
  • Quota (match sample to population on control categories, e.g., age, gender)
  • Consecutive (include every eligible subject until required size reached)

Probability Sampling (uses random selection)

• Ensures every population unit has equal chance.
• Limited by incomplete frames, time, or resources.
• Types:
  • Simple Random (assign numbers, draw via random method)
  • Systematic (select every k^{th} unit; k = \frac{N}{n})
  • Stratified (divide into strata; sample within each — proportional or disproportional)

Sample Size Guidelines

• Determined by method & study design.
• Focus group: 6{-}12 participants (not generalizable).
• Per variable cell: 50,\ 75,\ 100.
• Multivariate studies (total n):
  • 100 poor | 200 fair | 300 good | 500 very good | 1000 excellent.
• Allow extra 10{-}25\% for expected drop-outs (e.g., longitudinal studies).
• Fewer than 30 per cell ⇒ unstable results.

Sampling Error (Standard Error)

• Arises because sample data substitute for full population.
• Only calculable for probability samples.
• Must be estimated to understand result variability.