experimental design

• independent group design: participants are allocated to different groups where each group represents an experimental condition e.g ppl drinking red bull and water. simply - ppl split into groups and each group does only one part of the experiment. it is when 2 separate groups of participants experience two different conditions of the experiment.

  e.g ppl drinking energy drink - experimental condition

  ppl drinking water - control condition

  the performance of the 2 groups would then be compared
• repeated measures: all participants take part in all conditions of the experiment. so all participants experience both conditions.

  e.g each participant first experiences the energy drink condition, then each pt. is tested again later with water in the control condition. following this, two sets of data from both conditions would be compared to see if there was a difference. a repeated measure design is more reliable as it compares 'like with like.' whereas an independent gd assesses the performance of 2 different groups of people.
• matched pairs: pairs of participants are first matched on some variables (i.e age/gender/iq) that may affect the dependent variable. then one member goes in the experimental group and the other in the control group. participants are paired together on a variable relevant to the experiment

  E.g the 2 chattiest participants, then one pt. from each pair would be allocated to a different condition of the experiment. this is to control for the confounding variable of participant variables
• counterbalancing: an attempt to control for the effects of order in a repeated measures design

  • half the participants take part in condition A and then B and the other half take part in B then A (ABBA)
  • we use counterbalancing to prevent order effects from taking place
• order effects: when participant's responses to the various conditions are affected by the order of conditions to which they were exposed.

  i.e how the positioning of tasks affects the outcome e.g fatigue, practice.. orders can act as confounding variables
• independent groups

  • random allocation is used as an attempt to distribute participant characteristics/ variables across all conditions so they are less likely to effect the DV. this makes us more confident that the iv is causing an effect on the dv.
• independent groups design

  strengths -

  • no order effects as people only do one condition
  • demand characteristics are less likely as p's are only aware of own condition

  weaknesses -

  • p's are not the same in terms of participant variables which may introduce confounding variables. e.g a group could be more intelligent
• repeated measures

  strengths -

  • no participant variables as all key variables have been matched therefore higher validity
  • fewer p's are needed to be recruited as they are used twice

  weaknesses -

  • rise of order effects as p's take part in all conditions (fatigue, practice effect, recognising demand characteristics) can be overcome with counterbalancing
  • p's may work out the aim of the study which will lead to demand characteristics
• matched pairs

  strengths -

  • no order effects as p's only take part in one condition
  • less participant variables as p's have been matched up

  weaknesses -

  • time consuming and expensive to match up participants