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Bayesian explorations with dice
Author(s) -
Berg Arthur
Publication year - 2021
Publication title -
teaching statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.425
H-Index - 13
eISSN - 1467-9639
pISSN - 0141-982X
DOI - 10.1111/test.12271
Subject(s) - dice , computer science , bayesian probability , posterior probability , code (set theory) , bayesian statistics , bayesian inference , artificial intelligence , statistics , mathematics , programming language , set (abstract data type)
The topic of Bayesian updating is explored using standard and non‐standard dice as an intuitive and motivating model. Details of calculating posterior probabilities for a discrete distribution are provided, offering a different view to P ‐values. This article also includes the stars and bars counting technique, a powerful method of counting that is accessible to students who have been introduced to permutations and combinations. Supportive R code is included throughout, and a Shiny application accompanies the article allowing for an interactive exploration of the topics discussed.

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