1. Generalizations
    arguments with the conclusion that something is the case about all or many things on the basis of what is observed about some of them
  2. Basic Features of Generalization
    • Population
    • sample
    • target characteristic
    • representation
    • strength
  3. Population
    • group for which the conclusion is allegedy true
    • usually in the conclusion
  4. Sample
    • a premise or premises describing a subset of that population
    • group being studied
  5. Target Characteristic
    • main issue
    • the characterisitc observed in the sample and concluded to be true of the population
    • link btw population and sample
    • observed in the sample and inferred of population
  6. Representation
    critical analysis takes place
  7. Strength
    give the generalization a grade
  8. Evaluating Criteria: Representativeness
    • better representation of a sample, the stronger the generalizations
    • sample occur with the same frequency or in the same proportion as they occur in the population
    • implies a current knowledge-character and relevance
    • randomness is important
  9. Randomness
    • each member of the population has an equal chance of occurring in sample to not create a biased sample
    • mathematically defined
  10. Sampling Methodologies/Sample Selection and Constuction
    • Simple Random: fairly homogenous; TC presumed to be evenly distributed throughout the population
    • Stratified Random: heterogeneous groupings; TC not evenly distributed throughout the population
    • sample to be constucted
  11. Issues Affecting Strength of a Generalization
    • Representativeness of Sample
    • - Is it a biased sample?
    • - Sample size too small?
    • - Sample fails to reflect the diversity of the population
    • Inverview Bias
    • - Do questions skew the results?
    • - TC not clearly definded
    • - survey method skews results in a particular direction
Card Set
Phi 120 Final