Please enable JavaScript.

Coggle requires JavaScript to display documents.

Sampling (Cluster sampling (Units in the population can often be found in…

- - - - Doesn't need complete population information
      - Good for face-to-face surveys
      - Quick and easy
    - - Expensive if the clusters are large
      - Greater risk of sampling error
- - - - Subjects are readily available
      - Large amounts of information can be gathered quickly
    - - The sample is not representative of the entire population, so results can't speak for them - inferences are limited. future data
      - Prone to volunteer bias
- - - - Good for providing illustrative examples or case studies
    - - Samples often small
      - Cannot extrapolate from sample
      - Very prone to bias
- - - - Quick and easy way of obtaining a sample
    - - Not random, so some risk of bias
      - Need to understand the population to be able to identify the basis of stratification
- - - - Simple to design and interpret
      - Can calculate both estimate of the population and sampling error
    - - May not be practical if the sample requires lots of small visits over the country
      - Need a complete and accurate population listing
- - - - Easier to extract the sample than via simple random
      - Ensures sample is spread across the population
    - - Can be costly and time-consuming if the sample is not conveniently located