 Statistical model validation

Statistical model validation is the process of evaluating how well a statistical model performs in predicting outcomes based on unseen data. This process is crucial for ensuring that a model not only fits the training data well but also generalizes effectively to new, independent datasets. The goal of model validation is to assess the model's reliability, identify any limitations, and understand the conditions under which its predictions may be accurate or flawed.