Abstract:This article provides an applied introduction to Bayesian statistics for sociologists. Unlike frequentist statistics, which attaches repeated-sampling frequencies to test statistics, Bayesian statisti...This article provides an applied introduction to Bayesian statistics for sociologists. Unlike frequentist statistics, which attaches repeated-sampling frequencies to test statistics, Bayesian statistics directly describes uncertainty about unknown statistical parameters with a probability distribution. With this foundation, much of Bayesian statistics follows from basic rules of probability theory. Three areas of Bayesian statistics are especially relevant for sociologists. First, hierarchical regression models allow several levels of uncertainty into an analysis. Second, Bayes factors provide a useful approach to the problems of model selection, model averaging, and posterior inference about model indexes. Third, recent breakthroughs in estimation methods offer valuable new tools for analysis of Bayesian models that were previously intractable.Read More
Publication Year: 1999
Publication Date: 1999-08-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 40
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