High throughput screening (HTS) interrogates compound libraries to find those that are “active” in an assay. To better understand compound behavior in HTS, we assessed an existing binomial survivor ...

Repeated measures studies are frequently performed in patient-derived xenograft (PDX) models to evaluate drug activity or compare effectiveness of cancer treatment regimens. Linear mixed effects ...

Statistical modeling lies at the heart of data science. Well-crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In ...

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 ...

Interview with Dr. Caroline Buckee on the uses — and limitations — of epidemiologic modeling to predict the spread of Covid-19. 10m 49s Download Amid enormous uncertainty about the future of the Covid ...

A special review examines highly-cited papers in statistical ecology. The review, which covers a century of research, details how models and concepts have evolved alongside increasing computational ...

The last few years have been marked by dramatic increases in the volume and granularity of data available to marketers. User-level data can now be made available to marketers in near real-time and to ...

The Statistical & Data Sciences (SDS) Program links faculty and students from across the college interested in learning things from data. At Smith, students learn statistics by doing—class time ...

Applied Statistics is the implementation of statistical methods, techniques, and theories to real-world problems and situations in several fields, such as science, engineering, business, medicine, ...

Discover how insurers calculate loss cost, its role in determining premiums, and its impact on insurance profitability.