This chapter provides a treatment of popular Bayesian approaches to working with normal distribution models. We do not attempt a comprehensive account, instead providing a more cursory treatment that has two aims. First, it is valuable to review a number of Bayesian modeling concepts in the context of familiar normal distributions. Second, normal distributions are widely used in statistical and psychometric modeling. As such, this chapter provides a foundation for more complex models; in particular, the development of regression, classical test theory, and factor analysis models will draw heavily from the material introduced here.
As a running example, suppose we have a test scored from 0 to 100, and we are interested ...
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