An Overview of Large Language Models for Statisticians

Large Language Models (LLMs) are neural networks trained on extensive text corpora to model language. For statisticians, they are both an object of study – raising questions about generalisation, uncertainty, bias, and privacy and a practical tool for tasks such as data cleaning, synthetic data generation, and summarisation.

Statisticians can help design experiments, calibration methods, and evaluation metrics that reveal how LLMs behave under distribution shift or in high-stakes settings. They can also apply tools from causal inference, fairness analysis, and privacy-preserving statistics to improve reliability, interpretability, and protection of sensitive data