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 ...

Longitudinal data analysis encompasses a range of statistical methodologies that examine data collected over extended periods, enabling researchers to disentangle temporal effects and dynamic ...

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 ...

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 ...

While data is easier than ever to collect and store, knowing what to do with it and how to analyze it is a challenge, especially for those without the proper training. From boosting customer ...

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 ...

Design for parametric yield is becoming a key aspect of designing to improve yield. IC manufacturing processes are subject to fluctuations in electrical parameters, and these must be accounted for ...

The primary purpose of this short course is to illustrate the steps and the thought process statistical collaborators often go through when given a set of data analyze, particularly data that needs ...

It is no longer a mystery for designers and manufacturers of 45nm chips that higher process variability negatively impacts design performance, predictability and parametric yield. Manufacturing and ...

Statistical modeling techniques that retailers and manufacturers use to find and target customers helped some prognosticators predict the outcome of this month’s U.S. elections with stunning accuracy.