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Deprivation effect
When a survey measures what the participants want to have rather than what they actually have. ie. data collection processes measure desire rather than actual possession or behaviour.
Eg. a survey questions participants on how frequently they run. The survey mistakenly captures a participant’s desire to run as they over inflate their experiences.
Acquiescence bias
Refers to differences in the extent to which people generally tend to agree or disagree with a statement on a survey or questionnaire due to cultural influence.
Eg. If it was found that Canadians tend to agree more when answering survey questions. (will agree with both when presented with a scale rating with 2 differing questions: “I often experience social isolation” & “I am well connected to my social network”)
Reference group effect
When a participant compares themself to their peers within their culture. This comparison across cultures can vary significantly.
Moderacy and extremity bias
Similar people may rate themselves quite differently on surveys and questionnaires across cultures.
Eg. Participants who are ‘equally’ intelligent or creative
True Experimental Design
Involves the deliberate manipulation of an independent variable (X) to observe its impact on a dependent variable (Y), usually employing random assignment to control groups.
Pre-experimental Design
No control group OR no random assignment
Very weak internal validity
Cannot establish causation
Example: one‑group pretest–posttest
Quasi (‘Partial’) Experiment Design
Have a comparison group, but no random assignment
Stronger than pre‑experimental, but still not true experiments
Can suggest causal relationships, but with limitations
Example: non‑equivalent groups design
Between Subjects Design
Comparing different participants from different groups to each other (comparison of group A versus group B)
Within Subjects Design
The same group of participants take part in every condition.
(group A undergoes test 1, group A then undergoes test 2 and these results are compared)
Recall the WEIRD acronym to describe a demographic of research participants
W - westernised
E - educated
I - industrialised
R - rich
D - democratic
Factorial Design
A factorial study design is an experiment that tests two or more independent variables (factors) at the same time, allowing researchers to examine:
The effect of each factor on its own (main effects)
How the factors interact with each other (interaction effects)