research/experimental designs

• define independent measures design


  different participants are used for each level of IV (they are only tested in one condtion)
• define repeated measures


  when participants are tested in both IV conditions
• define matched pairs/participants 


  when participants are put into pairs as they are similar in one way and one of the pair is tested on one of the levels of IV (in most cases twins)
• weaknesses of repeated measures

  1. order effect could affect results
  2. as participants see the task more than once they have increased exposure to demand characteristics
• strengths of repeated measures

  • fewer participants. so is good when participants are hard to find
  • as each participant does all the IV levels, participant variables are unlikely to distort it
• strengths of matched pairs/participants

  • one level of the IV reduces the effect of demand characteristics
  • no order effects
  • individual differences are matched so participant variable = less likely to distort effect of IV
• weaknesses of matched pairs/participants

  • small sample size as availability of matching pairs is limited
  • similarity between pairs is limited by matching process so correct criteria must be chosen to prove effectiveness
• weaknesses of independent measures

  • more participants needed = less ethical if they are harmed + less effective if there is a small sample as they're hard to find
  • participant variables can distort results if there are important individual differences between participants in diff levels of IV
• strengths of independent measures

  • diff participants used in each IV level = reduces order effects
  • effect of demand characteristics reduces as ptcpns only see 1 IV lvl
  • random allocation of IV lvl = reduces effect of individual diffrences
• strengths of laboratory experiments

  • good control of extraneous variables
  • casual relationships = determined
  • standardised procedures raise reliability + allow replication
• weaknesses of laboratory experiments

  • artificial behaviour can make ptcpnts behaviour unrepresentative
  • ptcpnts cld respond to demand characteristics + alter behaviour
• strengths of field experiments

  • ptcpnts in normal situation + more likely to behave naturally = representative results
  • ptcpnts unaware they are in study = less problems w demand characteristics than lab experiments
• weaknesses of field experiments

  • controlling extraneous variables = harder in lab exp = low reliability + difficulty to replicate
  • researcher = less sure changes in DV are caused by changes in IV than in lab exp
  • ptcpnts = unaware they are in a study - raising ethical issues
• define order effects

  how order affects performance 
• define practice affects

  the amount of times someone does something can increase their performance
• strengths of quasi experiments

  • useful when unethical to manipulate IV
  • studies "real effects" so there is increased realism and ecological validity
• weaknesses of quasi experiments

  • must wait for IV to occur
  • can only be used where conditions vary naturally
  • ptcpnts = aware they are studies = less internal validity
  • confounding environmental variables = more likely = less reliable
• define individual differences


  unique characteristics + traits which distinguish us from others
• define participant characteristics


  any characteristics/ aspect of participants background that can affect study results even though its not the focus of the experiment
• define demand characteristics

  a high risk that a participant will change their natural behaviour to fit their interpretation of the aim of the study
• define environmental variables


  factors that exist in an individual's physical environment that influence behaviour