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 ...

When should you use an LLM over a statistical model? Three real-world cases reveal how data, representation, and training ...

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

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 ...

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 ...

This book, “Statistical Modeling and Computation,” provides a unique introduction to modern statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of ...

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 ...

In predictive modeling, future events are predicted based on statistical analysis. Read this guide to understand how predictive modeling works and how it can benefit your business. The rapid adoption ...

Predictive analytics allows data professionals to identify trends, forecast outcomes and test assumptions using data. When these capabilities are applied to simulation modeling, they make models more ...

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 ...