Not available at this time.

Informal discussion class, focusing on students' problems, concerns, or enthusiasm with their own experimental designs, data analyses, or interpretations of results, including computer- (particularly SAS) generated output. New techniques presented by the instructor or guest instructors as requested by the class. Students gain practical experience with data analysis and a better understanding of the approaches necessary for their own thesis or dissertation work. Prerequisite: PLNTSOIL 661 or other course in intermediate statistical analysis.

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

This course provides a calculus-based introduction to probability and statistical inference. Topics include the axioms of probability, sample spaces, counting rules, conditional probability, independence, random variables and distributions, expected value, variance, covariance and correlation, the central limit theorem, random samples and sampling distributions, basic concepts of statistical inference (point estimation, confidence intervals and hypothesis testing) and their use in one and two-sample problems.