modelling

Modelling (modelling in British English) is the process of creating abstract representations of real systems, processes, or concepts to study their behavior, test hypotheses, or make predictions. Models can be physical, such as scale models; mathematical, using equations; computational, implemented in software; or statistical, focusing on data-driven relationships. While the term is used across the natural sciences, engineering, economics, sociology, and policy analysis, the common aim is to understand how changing inputs affects outputs.

Modelling involves problem formulation, selecting an appropriate level of detail, constructing the representation of the mechanism, and estimating parameters from data. Models are then validated or verified by comparing predictions with observations, and uncertainties are quantified through sensitivity analysis, calibration, or cross-validation. Good modelling requires a balance between simplicity and realism; overly complex models risk overfitting, while overly simplistic models may miss key dynamics.

Applications range from climate and ecological forecasting to engineering design, financial risk assessment, epidemiology, and social research. In engineering, modelling supports design optimization and testing before construction. In science, models test hypotheses and project future scenarios under different conditions, often via simulation.

Limitations include reliance on assumptions, data quality, and the abstract nature of representations. Transparency, reproducibility, and clear communication of uncertainty are important. Ethical considerations arise when modelling informs policy decisions or affects individuals, groups, or ecosystems.