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 ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Bayesian quantile regression and statistical modelling represent a growing paradigm in contemporary data analysis, extending conventional regression by estimating various conditional quantiles rather ...

Here's a statistical challenge worthy of a grandmaster: How do you create an accurate ranking system when the best players ...

A range of genetic factors can influence the onset of diseases like high blood pressure, heart disease, and type 2 diabetes, according to scientists. If we were to know how the DNA influences the risk ...

A statistical model -- now an easy-to-use software tool -- local police can use to identify a series of related crimes and nab a suspect has been unveiled. Crime linkage is the investigative process ...

Researchers have developed a new statistical model that predicts which cities are more likely to become infectious disease hotspots, based both on interconnectivity between cities and the idea that ...

A new study published in the journal Science of The Total Environment has significant bearing on the hackneyed joke about chickens and their numerous reasons for crossing roads. In Florida, there's a ...

Bracket Breakers is written by Peter Keating and Jordan Brenner. This series identified the major upsets in each region, using their Slingshot model, which was developed alongside the Furman ...