CCJ 355 Lecture Notes - Lecture 5: Random Number Table, Nonprobability Sampling, Multistage Sampling

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Assess population diversity: need representative sample, one that looks similar (in all relevant aspects) to the population from which it is selected, consider a census information obtained though responses from all available members of a population. Stratified random sampling: all elements in population (sampling frame) sorted by relevant characteristic, elements randomly sampled within strata, distinguish individuals by race, within each racial category, sample individuals randomly, may sample proportionately or disproportionately. Multistage cluster sampling: may be used when no sampling frame available, extract random sample of groups (clusters, randomly sample individuals from within each cluster. Identify one member of population, ask him/her to identify others. Units of analysis and errors in reasoning. Individual: data collected from individuals and focus of analysis on individuals, group, data may be collected from individuals but combined (aggregated) to describe a group (neighborhood, school, prison, city, state, family, etc. )

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