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

From students prepping for exams to analysts refining workflows, AI is reshaping how statistics are learned and applied in 2026. Tools now walk users through concepts, run analyses, and assist with ...

The ability of developing complex internal representations of the environment is considered a crucial antecedent to the emergence of humans’ higher cognitive functions. Yet it is an open question ...

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

Predictive modeling of data using modern regression and classification methods. Multiple linear regression; logistic regression; pitfalls and diagnostics; nonparametric and nonlinear regression and ...

Scientists from Peking University conducts a systematic review of studies on integrating machine learning into statistical methods in disease prediction models. Researchers from Peking University have ...

A prior course in statistics at the level of IEMS 304; A course in matrix analysis; Proficiency in programming as coding will be a significant part of the class. This course examines a modern ...

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 ...

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

Discover how predictive analytics uses data-driven models like decision trees and neural networks to forecast outcomes and ...