Sample Generalizability
State why sample data have population implications
While a study collects data from a sample, conclusions are invariably applied to a population, e. g. a study of college students using browsers may conclude how "people" use browsers. The sample is the students who gave the data, but the population to whom conclusions are addressed is "people" in general. The researcher argues this generalization, from sample to population, by showing the sample is:
Big enough: Many subjects generalize better than few.
Representative: Reflects population distribution of gender, age or other relevant features, e. g. 50% female.
Unbiased: Was chosen from the population randomly.
e. g. 300 subjects were chosen at random with the same % male/female as the population is more representative than a few subjects chosen personally who are all male.
Alternatively, if the sample is not big enough, not representative or not unbiased in some way, then reduce the power of the generalization, e. g. a qualitative study may merely suggest "possible general implications", rather than imply them. Research that is more generalizable is relevant to more people.
Example(s)
(Use a descriptive name, e. g. "ITExample". Or click on an existing collection and edit it.)