Collaborative Data Science
BIC, or Bayesian Information Criterion, is a statistical tool used for model selection that estimates the quality of different models based on the likelihood of the data and the number of parameters in the model. It helps to penalize more complex models to avoid overfitting while still allowing for a good fit to the data. This makes BIC a vital concept in various types of statistical modeling, including regression analysis, time series forecasting, and model evaluation.
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