Extraneous variables and bias

• Participants


  Individual differences

  - ppts variables can become a problem especially in an independent measures design, creating random or constant confounding effect

  Method of control

  - repeated measures

  - matched pairs
• Method


  Artificial nature of situation

  - laboratory experiments and operationalised variables may lack ecological validity

  Method of control

  - field experiment
• Design


  Order effects

  - where learning, boredom or tiredness can influence the second condition of an experiment in a repeated measures design

  Method of control

  - counterbalancing - ABBA

  
  

  Demand characteristics

  - ppts respond to cues in environment and may try to work out the aim of study and adjust their behaviour

  Method of control

  - single blind, double blind

  - matched pairs

  - independent measures

  
  

  Investigator effects

  - expectations of researcher affect the results e.g. revealing the desired outcome to ppts or recording biased results

  Method of control

  - double blind

  - standardised instructions

  - natural experiment
• Procedure


  Distraction and Confusion

  - extraneous variables, not making things clear to ppt or experimenter being unsure of exactly what to do

  Method of control

  - standardised instructions

  - pilot study
• Examples of extraneous variables

  Participant variable

  - gender

  - age

  - intelligence

  - experience

  
  

  Participant reactivity

  - demand characteristics

  - Hawthorne effect

  - social desirability

  - motivation

  - order effects

  
  

  Situational variables

  - time of day

  - temperature

  - noise
• Single blind


  where the ppts don't know under which conditions they're being tested

  EV they aim to overcome

  - demand characteristics
• Double blind


  study is even more accurate if the experimenter doesn't know the conditions under which the ppts are being tested

  EV they aim to overcome

  - researcher bias
• Matched pairs design


  ppts are matched on relevant characteristics

  EV they aim to overcome

  - demand characteristics
• Standardised instructions


  a 'script' that's read to all ppts, ensuring consistency of instructions

  EV they aim to overcome

  - experimenter bias

  - increase reliability
• Counterbalancing


  used in a repeating measures design - ABBA

  EV they aim to overcome

  - order effects
• Pilot studies


  a trial run of a study on a much smaller scale

  AIM of a pilot study

  - identify anything that may go wrong in the real experiment

  - check aspects

  - ensures all variables are operationalised

  - check conditions of experiment