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An alternative teaching method of conditional probabilities and Bayes' rule: an application of the truth table
Author(s) -
Satake Eiki,
Vashlishan Murray Amy
Publication year - 2015
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.12080
Subject(s) - bayes' theorem , conditional probability , chain rule (probability) , truth table , table (database) , law of total probability , bayes' rule , computer science , artificial intelligence , mathematics , machine learning , posterior probability , bayes factor , algorithm , data mining , statistics , bayesian probability
Summary This paper presents a comparison of three approaches to the teaching of probability to demonstrate how the truth table of elementary mathematical logic can be used to teach the calculations of conditional probabilities. Students are typically introduced to the topic of conditional probabilities—especially the ones that involve Bayes' rule—with the help of such traditional approaches as formula use or conversion to natural frequencies. The truth table approach is an alternative method for explaining the concept and calculation procedure of conditional probability and Bayes' rule.