A big part of his work is figuring out when a statistical method is truly the best choice. Some problems have straightforward ...

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 ...

Looking to get into statistical programming but lack industry experience? We spoke with several statistical programmers from diverse backgrounds, and one thing became clear—there’s no single path to ...

What are the different types of predictive modeling? Your email has been sent Predictive modeling is a type of data mining that is used in a variety of situations and industries. This process involves ...

Researchers have created and preliminarily tested what they believe may be one of the first models for predicting who has the highest probability of being resistant to COVID-19 in spite of exposure to ...

In a recent article published in the eLife Journal, researchers launched a possum excreta surveillance program across 350 km 2 in the Mornington Peninsula near South Melbourne, Australia. The study ...

Positioned at the intersection of quantitative finance, statistical learning, and modern AI, the research addresses a ...