List of terms

    Posterior distribution

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    Definition

    A way to summarize one’s updated knowledge in Bayesian inference, balancing prior knowledge with observed data. In statistical terms, posterior distributions are proportional to the product of the likelihood function and the prior. A posterior probability distribution captures (un)certainty about a given parameter value.

    Related terms: Bayes Factor, Bayesian inference, Bayesian parameter estimation, Likelihood function, Prior distribution

    References:

    • Dienes, Z. (2014). Using Bayes to get the most out of non-significant results. Frontiers in Psychology, 5, 781. https://doi.org/10.3389/fpsyg.2014.00781
    • Lüdtke, O., Ulitzsch, E., & Robitzsch, A. (2020). A Comparison of Penalized Maximum Likelihood Estimation and Markov Chain Monte Carlo Techniques for Estimating Confirmatory Factor Analysis Models with Small Sample Sizes . https://doi.org/10.31234/osf.io/u3qag
    • van de Schoot, R., Depaoli, S., King, R., et al. (2021). Bayesian statistics and modelling. Nature Reviews Methods Primers, 1(1), 1–26. https://doi.org/10.1038/s43586-020-00001-2

    Originally drafted by: Alaa AlDoh

    Reviewed by: Adam Parker, Jamie P. Cockcroft, Julia Wolska, Yu-Fang Yang, Charlotte R. Pennington

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