Subject Variables:

  • want to include representative sample of individual differences
  • want sample to generalize to population
  • create a selection criteria
  • carefully choose criteria to avoid bias

Sampling Techniques:

  • simple random sampling
  • i.e., draw from hat
  • systematic random sampling
  • i.e., every other name
  • limitations exist
  • often topic limits, subjects unavailable

Sample Size:

  • N=population, n=sample
  • larger=more representative of populaton
  • larger=more likely to include all relevant subject variables
  • in laboratory, N=100, n=30
  • vulnerable to volunteer bias, mortality, sophistication

Controlling Subject Variables:

  • between-subject
  • within-subject
  • random assignment, counterbalancing, limit population
  • matched groups
  • repeated measures, pre/post-test