Research methods

• Independent groups design


  Ppts only go through 1 condition each, Usually randomly allocated
• Independent groups - pros

  No order effect, Less time consuming (if all conditions can be conducted simultaneously)
• Independent groups - cons

  More ppts needed than repeated measures, Risk of ppt variables affecting the results (extraneous variable)
• Repeated measures


  All ppts take part in all conditions
• Repeated measures - pros

  Results not subject to ppt variables, This means there’s higher internal validity
• Repeated measures - cons

  Risk of order effects (their experiences in previous conditions influence how they behave in the next ones), This can be fixed using counter balancing - 1 group does 1 condition first, another group does the other condition first
• Matched pairs


  Ppts go through 1 condition each, Matched w another ppt doing the other condition based on relevant characteristics (e.g. age)
• Matched pairs - pros

  No order effect Reduced risk of ppt variables
• Matches pairs - cons

  Complex & time consuming, Needs more ppts
• Independent variable


  Experimenter manipulates, Assumed to have a direct effect on DV
• Dependent variable


  The outcome or what is measured
• Operantionalising variables

  Making variable measurable/quantifiable E.g. can’t measure happiness but can measure how count how many times someone smiles, This makes it easier to replicate research
• Extraneous variables


  A variable that isn’t the IV but could have an effect on DV E.g. gender/age of ppt, demand characteristics
• Demand characteristics


  If the ppt works out the aims of the study, they may start acting differently & behave in a certain way E.g. in milgram‘s a study, they may have known the shocks were fake
• Qualitative data


  Any data that isn’t numerical
• Qualitative data - pros

  Flexible, Explores attitudes & behaviours in depth
• Qualitative data - cons


  Subjective - relies heavily on interpretation (subject to bias)Analysis can be time consuming
• Quantitative data


  Numerical data
• Quantitative data - pros


  Objective - not as subject to bias, Easier to analyse
• Quantitative data - cons

  Not as flexible, Can’t explore in depth as much
• Primary data


  Data collected for the purposes of the study
• Primary data - pros


  Specific to the researchers needs
• Primary data - cons

  Takes longer to gather, Expensive
• secondary data


  Information that has been collected by someone other than the researcher
• Secondary data - pros


  Takes less time to gather, Cheaper
• Secondary data - cons

  Not specific to researchers needs