Probability and statistics
Move from uncertain events to random variables, probability models and evidence-based statistical inference.
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Prior and likelihood combine into a posterior distribution through Bayes' rule.
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Bayes theorem relates conditional probabilities in opposite directions using prior probabilities and a nonzero evidence probability.
A credible interval contains a specified posterior probability under the Bayesian model.
Parameters maximize the likelihood of observed data within a specified model.
ANOVA partitions variation to test mean differences under model assumptions.
Autocorrelation measures dependence between a process and its lagged values.
Move from uncertain events to random variables, probability models and evidence-based statistical inference.