Grade Performance in Statistics: a Bayesian Framework
نویسندگان
چکیده
In this paper, we investigate questions involving the impact of a multitude of covariates and their interactions on the scores of a comprehensive exit exam from 121 undergraduate students in Texas State University via a hierarchical Bayesian mixture model. The model uses a mixture of Beta distributions, inflated for the purposes of modeling the behavior of students who are no-shows for the exam. We formulate the predictive probability distribution of letter grade test scores as well as the probability that a student will belong to a particular grade cluster given a set of covariate values.
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