Probability and statistics
Move from uncertain events to random variables, probability models and evidence-based statistical inference.
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A logistic link models binary-event probability through a linear predictor.
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Randomization, controls and replication structure studies to distinguish effects from confounding.
A response's conditional mean is modeled as linear in coefficients with assumptions about residuals.
ANOVA partitions variation to test mean differences under model assumptions.
Autocorrelation measures dependence between a process and its lagged values.
Bayes theorem relates conditional probabilities in opposite directions using prior probabilities and a nonzero evidence probability.
Move from uncertain events to random variables, probability models and evidence-based statistical inference.