1. How science works Investigating the difference between two conditions
i.e., An experiment

2. Experimental Design In an experiment we manipulate an IV
There are usually two values of the IV e.g.
Doing homework with background noise or doing it with no noise
Deep or shallow processing
These determine the conditions of the experiment
The conditions can be arranged different ways according to the design of experiment

3. Experimental Design 3 main types Independent measures
Repeated measures
Matched participants

4. Independent Measures Compare the results for the two groups
Recruit a group of participants
Divide them into two
This group does the experimental task with the IV set for condition 1
This group does the experimental task with the IV set for condition 2
Measure the DV for each group
Compare the results for the two groups

5. Repeated Measures Compare the results for the two conditions
Recruit a group of participants
Condition Condition 2
The group does the experimental task with the IV set for condition 1
The group repeats the experimental task with the IV set for condition 2
Compare the results for the two conditions

6. Matched Participants Compare the results for the matched pairs
Recruit a group of participants
Find out what sorts of people you have in the group
Recruit another group that matches them one for one
Treat the experiment as independent measures
Condition 1 Condition 2
Compare the results for the matched pairs

7. Problems with Independent Measures Design
Participant Variables – chance variation between participants can affect DV
E.G, in a test of a sample population’s mathematical ability, all participants in group 1 just happen to have a maths degree. In group 2, all participants happen to all be really bad at maths .
Could imply an effect where none exists (false positive)
Control by random assignment to groups
Use repeated measures or matched PPs instead

8. Problems with Repeated Measures Design
Carrying out a task repeatedly leads to changes in performance
Deterioration as PPs become tired or bored
Improvement due to practice
Solutions
Leave a long gap between conditions
Counterbalanced design
Use independent measures or matched participants

9. Counterbalancing Important control when using repeated measures
Reduces ‘carry over’ effects
Half PPs do condition A then B
Other half do condition B then A
Fully counterbalanced: ABBA