On Thursday, researchers published in Science the results of a study that tested an OpenAI model on diagnostic and clinical ...

Applied statistics is more than numbers—it’s a way to solve real-world problems in social science, healthcare, business, and beyond. From mastering research design to applying advanced data analysis, ...

Microsoft Excel's Analysis ToolPak add-in provides a range of statistical tools directly within the spreadsheet program. It supports descriptive and inferential analyses, scenario forecasting, and ...

Neurointervention has seen significant advancements in recent decades with the adoption of myriad new technologies and techniques. Initially reliant on case reports and small case series, we now ...

An AI lab called Fundamental emerged from stealth on Thursday, offering a new foundation model to solve an old problem: how to draw insights from the huge quantities of structured data produced by ...

Milestone articles have highlighted the frequency and types of statistical errors in research,1–5 yet fundamental errors persist across various disciplines. With a background in biostatistics and over ...

Abstract: Recently, many algorithms have been proposed to identify potential forced oscillation sources using synchrophasors. However, the synchrophasor coverage is limited in several systems, and the ...

If you’d like an LLM to act more like a partner than a tool, Databot is an experimental alternative to querychat that also works in both R and Python. Databot is designed to analyze data you’ve ...

The social science data analysis and visualization minor introduces students to the fundamentals and current innovations of research and data analysis across social science disciplines. It equips ...

The relentless march of artificial intelligence (AI) is not confined to Studio Ghibli memes and automated email responses. It is rapidly becoming a central pillar of national security strategy. The ...

Abstract: Accurate quality variable inference by process variables is the core of industrial inferential sensor modeling, where recent advancements have seen deep learning (DL) models achieving ...