Learn about econometrics, including how it uses statistical models and data analysis to test economic theories, forecast ...

Faculty develop methods for structured and unstructured biomedical data that advance statistical inference, machine learning, causal inference, and algorithmic modeling. Their work delivers principled ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

There is a persistent belief in the ‘AI’ community that large language models (LLMs) have the ability to learn and self-improve by tweaking the weights in their vector space. Although ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

Artificial intelligence systems based on neural networks—such as ChatGPT, Claude, DeepSeek or Gemini—are extraordinarily powerful, yet their internal workings remain largely a "black box." To better ...

Overview:  Statistics courses teach practical data analysis skills that can be used in real jobs and business ...

Researchers use statistical physics and "toy models" to explain how neural networks avoid overfitting and stabilize learning in high-dimensional spaces.

Physicists at Harvard University have developed a simplified, physics-inspired mathematical model to better understand how neural networks learn, potentially explaining why large AI systems often ...