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2. entire population is divided into groups before a random sample of these is collected e.g. geographically

  • Cluster sampling
  • Spatial sampling
  • Stratified sampling
  • Random sampling

3. population is divided into sub-populations and we expect the amount of intrest to vary between groups. samples are therefore taken from each sub-population

  • Stratified sampling
  • Cluster sampling
  • Random Sampling
  • Independent sampling

4. using stratified sampling over random sampling

  • is simpler to design and interpret
  • can increase accuracy
  • requires more visits around the population

5. a disadvantage of random sampling is that

  • it is prone to bias
  • you need a complete and accurate population listing
  • it is time consuming
  • it has a high risk of sampling error


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