Plants produce a wide diversity of compounds. Broadly, these are separated into primary metabolites, which are necessary for ...

LCGC International interviewed Bob Pirok from the University of Amsterdam, Netherlands to discuss strategies for enhancing ...

Recently, we spoke with Esther Olonimoyo from the University of Maryland, who recently published a study using high-performance liquid chromatography to analyze short chain fatty acids.

Methods to assess and address assumption violations are crucial in statistical model selection. Techniques like residual analysis, normality tests, and variance inflation factors are employed to ...

More information: Daniel R. Kowal et al, Monte Carlo Inference for Semiparametric Bayesian Regression, Journal of the American Statistical Association (2024). DOI: 10.1080/01621459.2024.2395586 ...

This Issue Brief surveys several key methods, including Benford’s Law, Bayesian finite mixture modeling, and outlier analysis, along with a range of other statistical techniques.

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding ...

The concept of statistical significance predated Gosset, but prior statisticians worked in the regime of large sample sizes. To appreciate why this distinction matters, we need to understand how ...

University of Barcelona. "Improving statistical methods to protect wildlife populations." ScienceDaily. ScienceDaily, 21 May 2024. <www.sciencedaily.com / releases / 2024 / 05 / 240521124615.htm>.