Experimental design

• Repeated measures design


  • all Ps partake in all conditions

  Strengths

  • P variables are less of a problem
  • less Ps needed, so less time consuming

  Weaknesses

  • order of tasks can influence results
  • more likely to work out aims if they do all conditions and so can result in demand characteristics
• Independent Measures


  • diff groups of Ps for each condition

  Strengths

  • reduce possibility of demand characteristics compared to a repeated design as Ps only do one condition

  Weaknesses

  • P variables are a greater issue
  • time consuming as the same amount of data must be generated for each participant
• Matched pairs


  • Ps are paired on key variables that affect the DV

  Strengths

  • Ps take part in one condition, so demand characteristics are less of a problem , as well as order effects
  • P variables are less of a problem as they are matched to another person

  Weaknesses

  • hard to match Ps exactly
  • time consuming to match
• Order effects


  • the order that tasks are done in may affect results
  • to control, use counterbalancing
  • Ps are split into two groups
  • one completes one condition first, the other will do condition two and then switch
• Participant variables


  • minimised by adding random allocations to conditions
  • placing names in a hat