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Selecting a sample (Quanlitative sampling (Criterion sampling (Fulfill…

- - - - guarantees desired representation of relevant subgroups within the sample
      - reduce selective bias
    - - Time consuming
      - Unable to used in certain cases when the population cannot be identify into subgroup
    - - Population
      - Sample size
      - Variable & strata
      - Classify
      - Select randomly
  - - - useful when the population is large
      - wide geographic area
      - feasible method
    - - Greater chance of the sample does not represent population
      - commonly used statistical method require randomly formed group
    - - Sample size
      - 3.Logical cluster
      - Population
      - List of population of clusters
      - Average number
      - Number of cluster needed
      - Select randomly
  - - - Consecutive number for all individuals
      - 5.Arbitrary number
      - Population list
      - Look at the number of digits that assigned
      - Sample size
      - The individual is in the sample when the number is same to a number assigned to an individual in the population
      - Population
      - Repeat step 6 and 7 until the desired number of individuals is fulfilled.
    - - Does not guarantee equal representation for the relevant subgroups
    - - Equal chance for all individuals
      - Free from bias
      - East to use and suitable in data analysis
  - - - Easy to construct
      - Efficient time and cost
    - - Certain subgroups maybe will be excluded out from the sample systematically
    - - List of population
      - K value
      - Sample size
      - Select randomly
      - Population