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 ...

Harvard University offers 7 free online Data Science courses covering visualization, probability, linear regression, modeling ...

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 ...

Retrieving an accurate picture of what a tagged animal does as it journeys through its environment requires statistical analysis, especially when it comes to animal movement, and the methods ...

An international team has developed statistical models to predict the risk of early death in patients being treated with non-intensive therapies for acute myeloid leukemia (AML). Results of analyses ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Google is expanding its AI model family while addressing some of the ...

Various statistical forecasting methods exist designed for use with slow-moving products, new product introductions, stable mature products and products with erratic demand. Determining which ...

This is a preview. Log in through your library . Abstract In this paper, we extend and analyze a Bayesian hierarchical spatiotemporal model for physical systems. A novelty is to model the discrepancy ...

For overweight or obese individuals without diabetes, but with pre-existing cardiovascular disease, semaglutide (Ozempic, Wegovy) is not cost-effective at current pricing, new research shows. However, ...