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 ...

The analysis of categorical data underpins inquiries across disciplines ranging from social sciences to genomics. At its core, categorical data analysis seeks to model relationships between variables ...

Machine learning and artificial intelligence wouldn't be possible without the statistical models that underpin their analytic capabilities. A Cornell statistician and his colleague have developed a ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

The following is a summary of a story that originally appears on the Trinity College of Arts & Sciences website. As a new assistant professor in Duke’s Department of Statistical Science, Lasse ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

An interdisciplinary team of University of Tennessee, Knoxville researchers recently published in Biophysical Journal on their development of a new statistical method that improves analysis in ...

In the 21st century, artificial intelligence (AI) has emerged as a valuable approach in data science and a growing influence in medical research, 4-6 with an accelerating pace of innovation. This ...

As artificial intelligence continues to reshape biomedical research, data-driven methods are opening new possibilities for understanding complex inflammatory ...