Research Methods

• Independent Variable 


  What you manipulate. It has at least 2 variables, often more, which can be assigned to different groups of participants, or used at different times
• Dependent Variable 


  What you measure. It needs to be quantifiable and preferably measured in some sort of standard unit.
• Hypothesis

  A clear, precise, testable statements that states the relationship or predicted outcome of the variables prior to the experiment taking place. This is different to the aim, which is a general statement about what the investigation is about.
• Non-directional


  Two tailed. Used when there is little or no previous research into an area
• Directional 


  One tailed. Used when the findings of previous research suggest a particular outcome
• Null


  A hypothesis that must be proved wrong
• Operationalise 


  To make your variables clear and measurable. It is really important to operationalise both the IV and DV when writing hypotheses
• Extraneous Variables 


  Nuisance variables which may interfere with the experiment
• Situational Variables 


  Aspects of the research situation other than the IV which may influence the DV
• Experimenter Variables 


  Effects of the experimenter's expectations which are communicated intentionally or unintentionally
• Participant Variables 


  Aspects of the participant's characteristics or experience (other than the IV) which may influence the DV
• Confounding Variables


  Variables that interfere with the effect of the IV. You could explain the results of the study (change in the DV) with a factor other than the IV
• Demand Characteristics 


  Participants work out whats going on in the experiment and change their behaviour-> how they behave is no longer natural
• Examples of demand characteristics 


  Please you effect

  Screw you effect
• Investigator/ Experimenter effects 


  Any unwanted influence of the investigator on the outcome (often subconscious)
• Double Blind trial


  Neither the researchers or the participants know which condition they are in. They are blind to the hypothesis and aims
• Randomisation


  Making as many things as possible random to reduce the investigator effect (eg, pull names out of a hat)
• Standardisation 


  Giving all participants the exact same environment, information and experience (eg instructions and timings)
• Experiment Type: Laboratory


  Highly controlled environment

  Not necessarily in a lab

  Researcher manipulates the IV and records the effect on the DV
• Field


  Takes place outside of the lab in a natural environment

  Basic scientific procedures are still followed

  Participants are randomly allocated

  IV is manipulated, other variables are constant
• Natural 


  Researcher makes use of naturally occurring variables

  Not a true experiment because the scientists cannot really manipulate the IV
• Quasi


  Almost like an experiment but not quite

  The IV is based on an existing difference between people

  No one manipulates the IV, it just exists
• Laboratory Strengths

  • Replication is more possible
  • Controlled environment
  • findings are valid
• Field Strengths

  • Higher mundane realism
  • Environment is more natural
  • More valid and authentic
  • High external validity
• Natural Strengths

  • Provides opportunity for researchers that may otherwise not have been undertaken
  • high external validity
• Quasi Strengths

  • Naturally occurring DV
  • Shares strengths with a lab experiment
• Laboratory weaknesses

  • Lacks generalisability
  • Artificial
  • low external validity
  • unnatural behaviour (demand characteristics)
  • low mundane realism
• Field weaknesses

  • Loss of control over CVs and EVs
  • Cause and effect of IVs and DVs may be more difficult to establish
  • Ethical issues
  • Invasion of privacy
• Natural weaknesses

  • Events may happen very rarely
  • Participants may not be randomly allocated to experimental conditions
  • May lack realism
  • Demand characteristics
• Quasi weaknesses

  • Confounding variables
  • IV is not deliberately changed by the researcher
  • Cannot claim that the IV has caused any observed change
• Independent groups 


  Two groups are used, one for each condition
• Matched participants

  like independent measures, but the two groups of participants are matched to be as similar as possible (eg age, sex...). This eliminates individual differences
• Repeated measures


  One group of participants is used to do both conditions
• Order effects


  The effects on the participant of doing one condition after another (may get bored so begin displaying demand characteristics)
• Individual differences 


  Natural variations between one group and the other (may effect the DV measurements)
• Counterbalancing


  Split groups in half and have on half do the conditions in one order and have the other group do the conditions on the opposite order, this eliminates order effects
• Independent groups strengths

  • Order effects are not a problem
  • Participants are less likely to guess the aims
• Repeated measures strengths

  • participant variables are controlled
  • Fewer participants are needed
• Matched pairs strengths

  • Order effects and demand characteristics are less of a problem
• Independent groups weaknesses

  • not the same in terms of participants
  • reduces the validity of the findings
  • Increased time and money spent on recruiting participants