Same as PLNTSOIL 793A; required of doctoral candidates.

Doctoral candidates attend weekly seminar meetings which cover various topics.

Master's candidates present results of their thesis research to faculty and graduate students at a specially scheduled seminar.

Master's candidates attend weekly seminar meetings which will cover various topics.

Selected research problems not related to a candidate's Master's thesis.

Graduate level independent project or research, unrelated to students' thesis or dissertation.

Not available at this time

Regression analysis is the most popularly used statistical technique with application in almost every imaginable field. The focus of this course is on a careful understanding and of regression models and associated methods of statistical inference, data analysis, interpretation of results, statistical computation and model building.

This course provides a forum for training in statistical consulting. Application of statistical methods to real problems, as well as interpersonal and communication aspects of consulting are explored in the consulting environment. Students enrolled in this class will become eligible to conduct consulting projects as consultants in the Statistical Consulting and Collaboration Services group in the Department of Mathematics and Statistics.

This course will introduce computing tools needed for statistical analysis including data acquisition from database, data exploration and analysis, numerical analysis and result presentation. Advanced topics include parallel computing, simulation and optimization, and package creation. The class will be taught in a modern statistical computing language.