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 modelling of graphical structures provides a principled framework for representing complex dependencies among multiple variables by means of graphs. In these representations, nodes ...

Statistical modelling of zero-inflated count data addresses datasets in which the frequency of zero outcomes exceeds that predicted by standard count distributions. Such phenomena arise across ...

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 ...

In this module, we will introduce the basic conceptual framework for statistical modeling in general, and linear statistical models in particular. In this module, we will learn how to fit linear ...

University of Cincinnati Cancer Center researchers report that a hybrid statistical and deep learning survival model ...

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 ...

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 ...

Ecosystem modeling for living marine resource management includes a range of qualitative and quantitative representations of part or all of an ecosystem. National Ecosystem modeling for living marine ...