in logic, derivation of conclusions from given information or premises by any acceptable form of reasoning. Inferences are commonly drawn (1) by deduction, which, by analyzing valid argument forms, draws out the conclusions implicit in their premises, (2) by induction, which argues from many instances to a general statement, (3) by probability, which passes from frequencies within a known domain to conclusions of stated likelihood, and (4) by statistical reasoning, which concludes that, on the average, a certain percentage of a set of entities will satisfy the stated conditions. See also deduction; implication.

in statistics, the process of drawing conclusions about a parameter one is seeking to measure or estimate. Often scientists have many measurements of an object—say, the mass of an electron—and wish to choose the best measure. One principal approach of statistical inference is Bayesian estimation (Bayes's theorem), which incorporates reasonable expectations or prior judgments (perhaps based on previous studies), as well as new observations or experimental results. Another method is the likelihood approach, in which “prior probabilities” are eschewed in favour of calculating a value of the parameter that would be most “likely” to produce the observed distribution of experimental outcomes.

In parametric inference, a particular mathematical form of the distribution function is assumed. Nonparametric inference avoids this assumption and is used to estimate parameter values of an unknown distribution having an unknown functional form.