A critical error in interpreting statistical data where associations observed at the aggregate or group level are incorrectly assumed to occur at the individual level.
A method for model selection that incorporates likelihood function and penalizes the complexity of the model. Notable examples are Akaike Information Criterion (AIC) and Bayes-Schwarz Information Criterion (BIC).