research methods

• aim


  a general statement of what the researcher intends to investigate, the purpose of the study
• hypothesis 


  a clear, testable statement that states the relationship between the variables to be investigated, made at the start of a study
• hypotheses can be directional or non-directional
• directional hypothesis


  states the direction of the difference or relationship, includes words like more or less, higher or lower etc
• non-directional hypothesis


  does not state the direction of the difference or relationship, simply states that there is a difference between conditions
• independent variable 


  variable that is manipulated by the researcher
• dependant variable 


  variable that we measure
• levels of IV


  different conditions
• operationalisation


  ensuring that variables are clearly defined so that it can be easily measured
• confounding variables 


  cause confusion, variable that is not the IV but varies systematically with the IV

  cannot tell if the changes in DV are due to the IV or the confounding variable
• extraneous variables


  any variables other than the IV which may affect the dependant variable if not controlled

  makes it more difficult to detect a significant effect
• participant variables


  any individual differences between participants that may affect the DV

  e.g. age, gender, motivation, IQ
• situational variables


  any features of the experimental situation that may affect DV

  e.g. noise, temperature, weather
• demand characteristics 


  a cue that makes participants unconsciously aware of the aims of a study or helps participants work out what the researcher expects to find
• please-you effect


  act in a way that they think i expected and over-perform to please the experimenter
• screw-you effect 


  deliberately underperform to sabotage the results of a study
• investigator effects


  anything that an investigator does that has an impact on a participants performance in a study other than what was intended
• randomisation


  minimise the effects of EVs and CVs

  use of random sampling to control for the effects of bias when designing an investigation

  attempts to control investigator effects
• standardisation


  all participants should be subject to the same environment, information and experience

  reduces EVs and CVs
• single blind procedure


  participants not told the aim of the study at the start to avoid demand characteristics
• double blind procedure 


  neither participants or researcher are aware of the aims, important feature in drug trials
• pilot studies


  a small scale trial run of a study to test any aspects of the design, in order to make improvements
• independent groups 


  participants are allocated to different groups where each group represents one experimental condition
• repeated measures 


  all participants take part in all conditions of the experiment
• matched pairs design 


  pairs of participants are first matched on some variables that may affect the dependant variables

  e.g IQ, age, education
• independent groups strengths

  • no order effects
  • demand characteristics are eliminated
  • saves time
• independent groups limitations

  • need multiple people
  • risk of unequal group size/distribution
• repeated measures strengths

  • participant variables reduced
  • good internal validity
• repeated measures limitations

  • less generalisable - less people
  • practice effect - get better second time doing it
  • takes longer
  • subject attrition
• matched pairs strengths

  • reduces participant variables
  • avoids order effects
• matched pairs limitations

  • cannot apply to everything e.g phobias
  • takes longer to find people
  • impossible to match people exactly
  • if 1 participant drops out, lose 2 participants
• laboratory experiments 


  conducted in highly controlled experiments, not always in a lab, researcher manipulates the IV and records the effects on the DV
• strengths of lab experiments

  • high control over confounding and extraneous variables
  • certain cause and effect
  • highly replicable
• limitations of lab experiments

  • artificial setting and tasks - low ecological validity and low mundane realism
  • demand characteristics as participants know they are being tested
• field experiments


  iv is manipulated in a natural, more everyday setting - participants usual environment rather than lab
• field experiments strengths

  • more natural setting - higher ecological validity
  • produce behaviour that is more authentic - participants are more likely to be unaware that they are in an experiment
• field experiment limitations

  • harder to control extraneous variables - lower internal validity
  • ethical issues if not aware of study as they cannot consent
• natural experiments


  researcher has no control over IV and cannot change it, IV is natural
• strengths of natural experiments

  • provide opportunities for research
  • high external validity
• quasi experiments


  IV is based on existing difference between people e.g gender, IV cannot be changed