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 ...

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

In the world around us, many things exist in the context of time: a bird's path through the sky is understood as different ...

Information on Earth's biodiversity is increasingly collected using DNA-, image- and audio-based sampling. At the same time, ...

This is a core course that provides essential grounding in statistical inference and modelling relating to science and food technology. Students will learn how to design, conduct, and analyse the ...

Surveillance data collected on several hundred different infectious organisms over 20 years have revealed striking power relationships between their variance and mean in successive time periods. Such ...

Information on Earth's biodiversity is increasingly collected using DNA-, image- and audio-based sampling. At the same time, new statistical analysis methods are being developed to make more out of ...

Throughout the years I have worked in credit and collections, either doing credit analysis related to commercial lending decisions or identifying the elements that should be weighed when reviewing ...

Researchers have created a statistical method that may allow public health and infectious disease forecasters to better predict disease reemergence, especially for preventable childhood infections ...

SEATTLE, WA, AUGUST 11, 2015 - 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 was unveiled today by Michael D.