Model Uncertainty

Model uncertainty refers to the doubt about how well a model represents the real world. In various fields, including science and economics, models are used to predict outcomes based on assumptions and inputs. However, these models may not fully capture all complexities or variations in reality. This uncertainty arises from factors like incomplete data, assumptions that may not hold true, or the inherent unpredictability of systems. Understanding this uncertainty is crucial because it helps researchers and decision-makers assess the reliability of predictions and make more informed choices.