Inferring

Inferring is the act of deriving a conclusion from evidence and reasoning. In everyday language, to infer means to make a reasoned guess about something not directly observed, based on what is known or observed.

In formal contexts such as logic, inference is the process of deriving a conclusion from premises according to a rule or a valid argument form. Different kinds of inference include deduction, induction, and abduction: deduction applies general rules to specific cases and yields conclusions that follow necessarily; induction generalizes from observed instances to broader generalizations, carrying probabilistic support; abduction proposes the most plausible explanation for the available evidence.

In statistics and data analysis, inference refers to drawing conclusions about a population or process from data samples. Statistical inference uses estimators, hypothesis tests, and confidence intervals to quantify uncertainty. Bayesian inference updates prior beliefs with data to form posterior beliefs. Distinguishing inference from prediction is common: inference concerns the properties of a population or mechanism, whereas prediction concerns future observations.

The process of inferring involves gathering evidence, assessing relevance, and weighing alternative explanations, while guarding against cognitive biases and the confusion of correlation with causation, overgeneralization, and sampling bias.

Inferring is central to the sciences, law, and everyday decision making, from interpreting experiments to assessing witness testimony or interpreting data models in machine learning, where a trained model infers labels or outcomes for new inputs.