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 it comes to statistics, we usually expect to be informed about what happens "on average." But sometimes the key information lies in deviations from that mean: how likely is heavy rain, and how ...

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 ...

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 ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

Demand is at an all-time high for data analysts who can help organizations, technology companies, governments, and nonprofit agencies grasp their organizational, societal, and scientific needs. The ...

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 ...

For humans and machines, intelligence requires making sense of the world — inferring simple explanations for the mishmosh of information coming in through our senses, discovering regularities and ...

In the 21st century, artificial intelligence (AI) has emerged as a valuable approach in data science and a growing influence in medical research, 4-6 with an accelerating pace of innovation. This ...