CRIM 220 Lecture Notes - Lecture 6: Simple Random Sample, Cluster Sampling, Statistical Parameter

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Probability sample: every member of population has a known probability of being included in the sample. Two reasons to sample: the logic of probability sampling probability. Each member of population has a known and equal chance of being selected. Contains same kind of variations that exist in the population. Estimate the degree of expected error probability sampling: selecting a sample that reflect variations that exist in population non probability. No way to estimate the probability each element has of being included in the population conscious and unconscious sampling bias. Sample of convenience easy but not representation. The more self-selection, the more bias representativeness and probability of selection. Representative characteristics of sample closely approximate those same characteristics in pop. Equal probability of selection method (epsem): all members of pop have equal chance of being selected probability theory and sampling distribution (p. 205) Translating abstract targets (e. g. , delinquents) to include definition and time referent.

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