To identify, foster and coordinate educational and research efforts in statistics among statisticians serving food and agriculture research programs, thus enhancing their relevance to collaborative research teams at their home institutions.
To mentor new faculty interested in pursuing a career in agricultural statistics and to educate other statisticians and administrators involved in the faculty evaluation process about the scholarship contributions of AES statisticians and their role in the scientific community.
To provide continuing statistical education to the scientific community through workshops and short courses, thus empowering scientists to conduct and evaluate research through the review and editorial processes.
To address technical concerns associated with the development of modern statistical methodology and its software implementation, as motivated by problems in food and agricultural research, including but not limited to:
Hierarchical models, including Bayesian models and generalized linear mixed models;
Meta-analyses characterized by multi-location, multi-investigator projects including those in which study treatments and/or designs may differ by location;
Big data and data science;
Interface between statistics, machine learning, and other predictive modeling strategies.