Model Fit

Model fit refers to how well a statistical or predictive model matches or explains the actual data observed. It indicates the accuracy of the model's predictions or assumptions. A good fit means the model closely represents real-world data, capturing key patterns without significant errors. Conversely, a poor fit suggests the model doesn't adequately capture the data's behavior, leading to unreliable predictions. Evaluating model fit helps determine whether the model is useful for understanding the data or making decisions. Essentially, it measures the alignment between the model's results and the real-world information it aims to represent.