Experimental design Flashcards
What is meant by a ‘Independent groups design’
Independent groups – where each group only participates in one of the conditions. For example. In an experiment seeing if men or women are faster. Obviously, the men can only compete in the men’s category.
Evaluate Independent groups design
Strength: Reduced likelihood of demand characteristics as the participants are only taking place in one condition rather than both.
Weakness: Doesn’t account for participant variables / differences as the participants only take place in one of the conditions.
What is meant by a ‘Repeated Measures Design’
Repeated measures where each group participates in both of the conditions. For example. Seeing if people run faster after a red bull or water. The group runs after water then the week after runs after red bull.
Evaluate Repeated measures design
Strength: Participant Variables are kept constant between conditions as the same participants take part in both conditions.
Weakness: Doesn’t account for practise element. People might naturally do better on the 2nd condition as they have done the task once already.
What is one way to help negate the practise element of repeated measures?
Counterbalancing is when in a repeated measures we account for the practise element. There are two ways of dealing with this:
AB BA method involves having 2 groups who participate in both conditions. One starting in condition A first and B second. And the other group starting with B and doing A after.
ABBA involves one group, but each participant takes part in the same condition twice.
What is meant by a ‘Matched Pairs Design’
Matched pairs are where two groups of participants are matched on characteristics that are believed to affect performance. For instance, gender, height, weight, age, iq. Ect.
Evaluate Matched Pairs design
Strength: High control over any participant variables as they are matched based on their characteristics that could affect the study.
Weakness: Can be EXTREMELY time consuming to find participants who fit all the necessary characteristics. And its impossible to match them fully due to participant variables such as amount of sleep.
