BIC (Bayesian Information Criterion)

The Bayesian Information Criterion (BIC) is a statistical tool used to evaluate and compare different models for a given set of data. It balances model fit and complexity: models that explain the data well are favored, but overly complex models risk overfitting. The BIC produces a numerical value; lower values indicate a better model based on the trade-off between accuracy and simplicity. Essentially, BIC helps researchers choose the most appropriate model by penalizing those that are unnecessarily complicated while rewarding those that provide a good fit to the data.