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Bayesian inference

Prior and likelihood combine into a posterior distribution through Bayes' rule.

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  • Bayes theorem

    Bayes theorem relates conditional probabilities in opposite directions using prior probabilities and a nonzero evidence probability.

  • Credible intervals

    A credible interval contains a specified posterior probability under the Bayesian model.

  • Maximum likelihood

    Parameters maximize the likelihood of observed data within a specified model.

  • Analysis of variance

    ANOVA partitions variation to test mean differences under model assumptions.

  • Autocorrelation

    Autocorrelation measures dependence between a process and its lagged values.

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Probability and statistics

Move from uncertain events to random variables, probability models and evidence-based statistical inference.

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