Using predictive Bayesian Monte Carlo- Markov Chain methods to provide a probablistic solution for the Drake equation

Abstract

Are we alone in the universe? It is an age-old question that continues to encourage interest and controversy among the public as well as academics. Development of explanations for life elsewhere ranges widely, but few mathematical models have been developed to measure the likelihood of concurrent, intelligent life, and those that exist are widely speculative due to the lack of information. However, with the addition of information from Kepler explorations for new solar systems within our galaxy, and calculation of the potential number of stars in the expanse of the universe, data for a useful probabilistic model to determine the likelihood of life beyond Earth may be possible with the use of predictive Bayesian statistics. Predictive Bayesian statistical methods are designed to use limited, uncertain data, to develop results. The result provides a probability curve of the likelihood of life in the universe that includes both uncertainty and potential variability within the result to provide a means to define the probability of life in the galaxy as well as life within proximity to earth. That said, the results indicate that the probability we are alone (<1) in the galaxy is significant, while the maximum number of contemporary civilizations might be as few as a thousand. With so few concurrent civilizations, and such large distances, it is little surprise that the SETI project has not found that alien signal. Our nearest neighbor is 4 light years away, and there are under 100 stars within 50 light years, the total of the project's existence.