causalitate

Causalitate, or causality, is the relation in which one event or state (the cause) brings about another event or state (the effect) or changes its probability. In everyday language and in science, causal claims rely on temporal order, covariation, and the presence of an underlying mechanism that links cause and effect.

Key questions in causal thinking include whether a cause is necessary or sufficient for an effect, whether changes in one variable alter the likelihood of another, and whether the relationship can be demonstrated through intervention or manipulation. Philosophical theories of causation range from Humean regularities to counterfactual analyses and interventionist approaches that emphasize manipulable connections between actions and outcomes.

In practice, causal inference uses a variety of methods. Randomized controlled trials and experiments aim to isolate causal effects, while observational studies control for confounding factors. Formal tools such as do-calculus, propensity score methods, and structural equation models help formalize assumptions and estimate causal relationships. In time-series analysis, concepts like Granger causality assess whether one variable improves the prediction of another, though this does not guarantee true causation.

Causal notions appear across disciplines. In physics, causality is constrained by the structure of spacetime and signals propagating at or below the speed of light. In statistics and computer science, causal graphs and Bayesian networks model dependencies and enable reasoning about interventions. In linguistics and law, causality informs the interpretation of actions, events, and responsibility. The Romanian term causalitate is commonly used to refer to these ideas in various contexts.