EXPERIMENTAL DESIGN

• Experimental design:

  • Refers to how many conditions of the IV each participant will experience
• INDEPENDENT GROUPS:

  • A group of participants are recruited and divided into 2
  • First group- does experimental task with the IV set for condition 1
  • Second group- does the experimental task with the IV set for condition 2
  • DV is measured, results are compared
• STRENGTHS AND WEAKNESSES OF INDEPENDENT GROUPS

  STRENGTHS: 

  • Reduces the impact of order effects e.g. fatigue (only do one condition of the IV)

  WEAKNESSES: 

  • Comparing groups with different characteristics e.g. age / gender, lots of people needed
• REPEATED MEASURES: 

  • Participants are recruited (1 group)
  • Experimental task- done with the IV set for condition 1, same for condition 2
  • Do both conditions of the IV
  • DV measured- results are compared
• STRENGTHS & WEAKNESSES OF REPEATED MEASURES:

  STRENGTHS:

  • Fewer people are needed as they take part in all conditions, People take part in all conditions, reduces individual differences

  WEAKNESSES:

  • Order effects e.g. fatigue / boredom
• MATCHED PAIRS DESIGN:

  • Group of participants are recruited, each participant is matched with another participant that has one shared variable (relevant to the study, can impact the DV if it isn’t controlled)
  • The pairs are randomly allocated to 1 level of the IV
  • Then treated like an independent groups design- results are compared
• STRENGTHS AND WEAKNESSES OF MATCHED PAIRS:

  STRENGTHS:

  • Avoids order effects

  WEAKNESSES:

  • Time-consuming
  • Lose 2 participants’ data if 1 participant drops out
  • Participant variables- can’t match people exactly
• ORDER EFFECTS:

  • Fatigue (decreases performance)
  • Boredom (decreases performance)
  • Practice (increases performance)
  • Order effects impact the data rather than the IV
  • Reducing the impact of order effects -> counterbalancing
• EXPERIMENTAL CONDITION:

  • Level of the IV that is manipulated by the researcher in order to assess the effect on a dependent variable (e.g. receiving actual drug of interest)
• CONTROL CONDITION:

  • Does not involve exposure to the treatment / intervention under study (e.g. receiving a placebo)
• Causality:

  • Manipulation of the IV will determine the outcome on the DV-> cause and effect can be established
  • Something has a cause- must be a law to describe the cause
  • Formation of laws / causes- scientists can predict / control future events