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Random Sample

Unlike a census, where data is collected from every member of the population, a random sample involves collecting data from a small, representative group from within the population. In a purely random sample, every unit of the population has an equal chance of being selected, removing bias from the selection procedure.

To conduct a random sample, a population is first defined, as well as a target sample size. Units of the population are then chosen at random.

Because the selection is random, the sample is assumed to be representative of the population, and the information collected can be used to develop inferences about the whole population. Random samples can effectively be used to gain insights into a very large population, where a census is impossible to conduct. However, conducting a truly random sample may be challenging where the population is large, dispersed, or hidden. Furthermore, random sampling may not be feasible or ethical when dealing with populations that are marginalized or criminalized. If not conducted properly, random sampling may be subject to bias.

The Human Rights Data Analysis Group has used random sampling to conduct a number of large-scale, post-conflict body counts.