Logic and statistics

Inferences are steps in logical reasoning, moving from premises to logical consequences; etymologically, the word infer means to "carry forward". Inference is theoretically traditionally divided into deduction and induction, a distinction that dates at least to Aristotle (300s BC). Deduction is inference deriving logical conclusions from premises known or assumed to be true, with the laws of valid inference being studied in logic. Induction is inference from particular evidence to a universal conclusion. A third type of inference is sometimes distinguished, notably by Charles Sanders Peirce, c

method of statistical inference

process of deducing properties of an underlying probability distribution by analysis of data

method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available

mathematical relationship in which two or more events or variables are associated but not causally related, due to either coincidence or the presence of a certain third, unseen factor

method of estimating the parameters of a statistical model

in statistics, a non-significant result

non-deductive syllogism