You know you've been dying to perform complicated statistical analyses. The R programming language might just be your ticket to success. Dave Rosenberg has more than 15 years of technology and ...

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 ...

The following is a summary of a story that originally appears on the Trinity College of Arts & Sciences website. As a new assistant professor in Duke’s Department of Statistical Science, Lasse ...

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 ...

SERC copy Purchased with Adopt-a-Book funds. "Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the ...

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 ...

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 ...