Biological and Agricultural Applications

The general area of biological and agricultural statistics includes a wide variety of methodologies. For example, general linear models, analysis of variance techniques and design of experiments were largely developed for the purpose of maximizing yield in agricultural applications. Statistical methodology continues to develop and respond to new technology that allows for the collection of new kinds of data. Precision agriculture uses spatial methods, mixed models and repeated measures to handle large quantities of data.

Ecological statistics allow us to make inferences about plant and animal population sizes and abundances using methods like capture-recapture. The area of biological and agriculture statistics encompasses methods motivated by application so that researchers can make the most of the data collected, whether from designed experiments or observational studies.

Faculty

Sujit Ghosh
Emily Griffith
Kevin Gross
Marcia Gumpertz
Jason Osborne
Brian Reich
Charlie Smith
Jonathan Stallrich