title: A Pragmatic Bayesian Perspective on Correlation Analysis : The exoplanetary gravity - stellar activity case.
abstract: We apply the Bayesian framework to assess the presence of a correlation between two quantities. To do so, we estimate the probability distribution of the parameter of interest, ρ, characterizing the strength of the correlation. We provide an implementation of these ideas and concepts using python programming language and the pyMC module in a very short (∼ 130 lines of code, heavily commented) and user-friendly program. We used this tool to assess the presence and properties of the correlation between planetary surface gravity and stellar activity level as measured by the log([Formula: see text]) indicator. The results of the Bayesian analysis are qualitatively similar to those obtained via p-value analysis, and support the presence of a correlation in the data. The results are more robust in their derivation and more informative, revealing interesting features such as asymmetric posterior distributions or markedly different credible intervals, and allowing for a deeper exploration. We encourage the reader interested in this kind of problem to apply our code to his/her own scientific problems. The full understanding of what the Bayesian framework is can only be gained through the insight that comes by handling priors, assessing the convergence of Monte Carlo runs, and a multitude of other practical problems. We hope to contribute so that Bayesian analysis becomes a tool in the toolkit of researchers, and they understand by experience its advantages and limitations.
authors.affiliation: Instituto de Astrofísica e Ciências do Espaço, Universidade do Porto, CAUP, Rua das Estrelas, 4150-762, Porto, Portugal. pedro.gueira@astro.up.pt.
authors.forename: P
authors.initials: P
authors.lastname: Figueira
authors.affiliation: Instituto de Astrofísica e Ciências do Espaço, Universidade do Porto, CAUP, Rua das Estrelas, 4150-762, Porto, Portugal.|Departamento de Física e Astronomia, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, 4169-007, Porto, Portugal.
authors.forename: J P
authors.initials: JP
authors.lastname: Faria
authors.affiliation: Instituto de Astrofísica e Ciências do Espaço, Universidade do Porto, CAUP, Rua das Estrelas, 4150-762, Porto, Portugal.
authors.forename: V Zh
authors.initials: VZ
authors.lastname: Adibekyan
authors.affiliation: Instituto de Astrofísica e Ciências do Espaço, Universidade do Porto, CAUP, Rua das Estrelas, 4150-762, Porto, Portugal.|Institut für Astrophysik, Georg-August-Universität, Friedrich-Hund-Platz 1, 37077, Göttingen, Germany.
authors.forename: M
authors.initials: M
authors.lastname: Oshagh
authors.affiliation: Instituto de Astrofísica e Ciências do Espaço, Universidade do Porto, CAUP, Rua das Estrelas, 4150-762, Porto, Portugal.|Departamento de Física e Astronomia, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, 4169-007, Porto, Portugal.
authors.forename: N C
authors.initials: NC
authors.lastname: Santos
mesh_terms: D001499:Bayes Theorem; D006112:Gravitation; D009010:Monte Carlo Method; D016083:Planets; D012984:Software; D055609:Stars, Celestial
keywords: Correlations; Exoplanets; Statistics; Stellar activity