Experimental design

• Random allocation – An attempt to control participant variables in an independent groups design which ensures that each participant has the same chance as being in one condition as any other
• Randomisation - not to manipulating everything in sight. Experiments will otherwise be biased.
• Counterbalancing - An attempt to control order effects (e.g. practice or fatigue) in a repeated measure design: half the participants experience the conditions in one order and the other half in the opposite order
• Standardisation - keeping variables consistent and the same
• • In an experiment, in order to find out if the IV did affect the DV, we need to have a comparison condition – where there is a different level of IV.
  • The way that the two levels of IV are delivered is called experimental design - It often refers to how participants are allocated to the different conditions (or IV groups) in an experiment.
• Repeated measures is when the same participants take part in each condition of the independent variable. (All p’s receive the same level of IV):

  • This means that each condition of the experiment includes the same group of participants.
  • The scores from both conditions are then compared to see if there is a difference.
• Independent measures/groups is when different groups of participants experience different conditions of the independent variable. (Each group does 1 level of the IV):

  • This means that each condition of the experiment includes a different or separate group of participants.
  • The performance of the two groups would then be compared.
• Matched pairs design is when each condition uses different participants, but they are matched in terms of certain characteristics (e.g. sex, age, intelligence etc.) believed to affect performance on the DV.
• Repeated strengths:

  • No group differences; extraneous variables are controlled
  • Fewer P’s needed
• Repeated weaknesses:

  • Order effects (fatigue/boredom/practice)
  • Lost P’s from both conditions
  • Demand characteristics
• How to overcome Repeated weaknesses:

  • Counterbalancing ‘ABBA’

  Or

  • Condition A then B Condition B then A
• Independent strengths :

  • No order effects
  • Less chance of demand characteristics
  • Saves time-P’s tested at the same time
• Independent weaknesses:

  • More P’s needed
  • Group differences - can affect the DV (extraneous variables)
• How to overcome independent weaknesses:

  • Random allocation of p’s minimises group differences
• Matched pairs strength:

  • Group differences are minimised
• Matched pairs weaknesses:

  • Matching difficult
  • Time-consuming on finding matching p’s unless they're identical twins
• How to overcome matched pairs weaknesses:

  • Restrict the number of variables to match on to make it easier
  • Conduct a pilot study to consider key variables that might be important when matching
• Counterbalancing:

  • The purpose of counterbalancing is to ensure both conditions (Task A and B) are tested first and second in equal amounts.
  • The purpose of this is to avoid order effects which could include practice effects, where participants perform better on their second trial, or fatigue/boredom effects, where participants perform worse on their second trial.
  • By ensuring that half of the participants complete Task A first followed by B and the other half complete Task B first followed by A, then any order effects are balanced