A **saturated model** is a statistical model that is fully specified to account for all possible variability in the data. In essence, it includes as many parameters as there are data points, meaning that it can fit the data perfectly. Thus, every possible outcome in the dataset is accounted for by a unique parameter within the model. Here are some key points about saturated models: 1. **Overparameterization**: Saturated models typically have a high number of parameters, making them overparameterized.
