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random sampling
selecting participants from the population randomly so that each member of the population has an equal chance of being selected
stratified sampling
dividing the population into subgroups, then randomly selecting participants from each subgroup
qualitative data
data that is characterised and catogorised
quantitative data
data that can be measured numerically
within subjects design
all participants in the sample being involved in both experimental and control conditions
between subjects design
participants are randomly allocated to either control or experimental conditions
mixed design
combines between subjects and within subject designs
disadvantage of between subjects design
time consuming as groups had to be tested at separate times
disadvantage of within subjects design
practice effect - prior participation in the first condition may influence their behaviour while completing the second condition
advantage of within subjects design
no participant variables between groups, improving validity
advantage of between subjects design
lower rate of participant withdrawal because participants only complete one condition