Abstract: The purpose of this methods and concepts tutorial is to present the homodyned K-distribution (HKD) statistical modeling of the echo envelope of received radio frequency (RF) signals in the ...

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 ...

Purdue University’s online Master's in Applied Statistics prepares students to advance theory, methods and computing for the purpose of meeting today’s emerging science and technology by including ...

The Labor Department’s internal watchdog is investigating how the Bureau of Labor Statistics collects and reports economic data as a part of an effort to better understand how the U.S. economy is ...

Graphical Abstract: We developed a mechanistic model to simulate purification of a viral-protein complex by cation-exchange chromatography on the “wrong side” of the molecule’s isoelectric point (in a ...

City Science, a rapidly expanding profession, is the scientific study and engineering of urban systems. It uses advanced technologies, big data, and complex systems physics to tackle challenges such ...

A new ranking methodology places Barry Bonds over Babe Ruth as the game’s best player ever. Statisticians, at least, are cheering. By Alexander Nazaryan Every sport has its arguments over which player ...

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 ...

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 ...

Many of us are proud to have learned sophisticated statistical methods like structural equation modeling and multilevel modeling and are eager to use these methods to test increasingly sophisticated ...