The Role of Real and Synthetic Data in Modeling

When creating models to represent real-world phenomena, the use of real data is essential, although synthetic data often plays a critical role during the development phase. By generating synthetic data, practitioners can ensure that their models accurately capture the expected behavior of real data. For instance, if a model aims to calculate the mean of a dataset, it can be tested with synthetic data that is known to have a specific mean. This process allows for initial validation and debugging of the model before applying it to actual data, enhancing the reliability of the outcomes produced.