What does AIC stand for?

What does AIC stand for?

• A. AICC
• B. Schwarz information criterion
• C. A Akaike's information criterion
• D. Adjusted information criterion

Answer: (C)

AIC stands for Akaike Information Criterion. It's a model-selection tool that weighs how well a model fits the data against how complex it is, penalizing extra parameters to avoid overfitting. In practice, you compare the AIC values across candidate models and prefer the one with the smallest value. The standard name is Akaike's Information Criterion, which is why the option phrased as "A Akaike's information criterion" is the best match. The other choices refer to related or different criteria: AICC is a small-sample corrected version of AIC, Schwarz information criterion is the Bayesian Information Criterion (BIC), and an adjusted information criterion isn’t the standard term used here.

AIC stands for Akaike Information Criterion. It's a model-selection tool that weighs how well a model fits the data against how complex it is, penalizing extra parameters to avoid overfitting. In practice, you compare the AIC values across candidate models and prefer the one with the smallest value. The standard name is Akaike's Information Criterion, which is why the option phrased as "A Akaike's information criterion" is the best match. The other choices refer to related or different criteria: AICC is a small-sample corrected version of AIC, Schwarz information criterion is the Bayesian Information Criterion (BIC), and an adjusted information criterion isn’t the standard term used here.