Why AI Threat Models In Finance Must Follow The Data, Not The Code

For financial institutions, threat modeling must shift away from diagrams focused purely on code to a life cycle view ...
BMJ

Causal inference is hard, and advanced statistical analysis is not enough

Health researchers need to fully understand the underlying assumptions to uncover cause and effect. Timothy Feeney and Paul Zivich explain Physicians ask, answer, and interpret myriad causal questions ...
ischool.berkeley.edu

The Landscape of College-Level Data Visualization Courses, and the Benefits of Incorporating Statistical Thinking

Branson, Z., Paz Parra, M., & Yurko, R. (2025). The Landscape of College-Level Data Visualization Courses, and the Benefits of Incorporating Statistical Thinking. Journal of Statistics and Data ...
IEEE

Statistical Inference With Limited Memory: A Survey

Abstract: The problem of statistical inference in its various forms has been the subject of decades-long extensive research. Most of the effort has been focused on characterizing the behavior as a ...
ki.se

Causal inference for epidemiological research

be able to use counterfactuals to express and interpret causal queries; be able to judge when standard statistical methodology is appropriate for causal inference, and when it is not; be able to use ...
Scientific Research Publishing

Hastie, T., et al. (2009) The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Vol. 2, Springer, New York.

ABSTRACT: Cardiovascular Diseases (CVDs) pose a significant global health challenge, necessitating accurate risk prediction for effective preventive measures. This comprehensive comparative study ...
Inside Higher Ed

Students Distancing From Distance Learning

The number of students participating in online learning is continuing a post-pandemic decline, new enrollment data show. In the 2022–23 academic year, a little over half of U.S. students—53 ...