The previously written article, Bayes Theorem - An Introduction, was the first in a line of planned articles with the goal of exploring Bayes' Theorem and Bayesian Analysis in greater and greater detail. It was felt, however, that it might be helpful for those interested to get a feel of Bayes' Theorem in action. That is, seeing it work independent of any formulaic (or theorectical) use. That was the motivation (and inspiration) for the development of BayesSim.
I am firm believer in the idea that the understanding of the concepts is more important - and certainly more relevant - than just being able to plug numbers into a formula. The use of modeling and simulation is an excellent way to seek and gain conceptual knowledge. BayesSim was developed to simulate the environment of a problem and to reach a conclusion based solely on probability definitions. This allowed for the exploration of what it means to assess two competing hypotheses given new data in a simulated (even practical) way. It is hopeful that seeing the results of the simulation mirror the direct computation via Bayes' Theorem will provide a deeper understanding and appreciation, not to mention an increase in the confidence in and respect for the beauty and power of Bayes' Theorem.
Bayes's Theorem - A Simulation