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C19: Population & Sampling Procedures, Snowball Sampling - Coggle…

- - - - Subjects are chosen to be part of the sample
      - Believes that some subjects are fit for research compared ton other individuals
    - - Involves assembling of sample with known/demonstrable experience
      - Pros- not out of your own trying to defend your decision
      - Cons- The experts can be wrong
    - - Sample respondents of one/more specific predefined groups
      - Benefit: useful when proportionality is not primary concern, are likely to get opinions of target population
    - - Ensure equal/proportionate representation of subjects depending on trait
      - People non-randomly is selected
      - Types: Proportional & Non-proportional
    - - Easiest, cheapest, least time consuming, asking volunteers
      - Problem: no evidenced that they are representative of populations
    - - Include all opinions/views & present proportionately
      - Term- Sampling for diversity
  - - - Often used than random sampling that apply an equal-probability method
      - Population has known & equal probability
    - - The population is divided into mutually exhaustive subsets
      - Steps: Divide population into clusters, randomly sample clusters, measure all units within sampled clusters
    - - Involves dividing population into subgroups based on variables known
      - Pros- enable researchers to draw inferences on specific subgroups that may lost in more generalizes random sample
      - Cons- Increase cost & complexity of sample selection
    - - Simple, stratified, systematic & cluster
    - - All subsets are given equal chance/probability of being included
      - Pros- easy to apply in research activities
      - Cons- Standard errors of estimators can be high