The purpose of statistical model selection is to identify a parsimonious model, which is a model that is as simple as possible while maintaining good predictive ability over the outcome of interest.

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 ...

R is a powerful open source programming environment primarily known for its statistical capabilities. In this course we will cover some advanced applications of R: distributed computing using the ...

Statisticians generally consider statistical modeling superior (or at least a useful supplement) to experience-based intuition for estimating the outputs of a complex system. But recent psychological ...

The mission of Technometrics is to contribute to the development and use of statistical methods in the physical, chemical, and engineering sciences. Its content features papers that describe new ...

Information on Earth's biodiversity is increasingly collected using DNA-, image- and audio-based sampling. At the same time, ...

'Genomic prediction' has been used by researchers to predict the performance of hybrid rice. Genomic prediction is a new technology that could potentially revolutionize hybrid breeding in agriculture.

2 School of Exercise Science, Australian Catholic University, Brisbane, Queensland, Australia 3 School of Human Movement Studies, The University of Queensland, Brisbane, Queensland, Australia 4 ...