Doctoral candidates attend weekly seminar meetings which cover various topics.

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

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.

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

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

Supplies background necessary to design and analyze field and laboratory experiments. Focus on statistical analysis for biological scientists. Primary emphasis on analysis of variance, regression, and experimental design. Computer-assisted analysis experience provided.

Prerequisites: a course in basic statistical analysis.

Supplies background necessary to design and analyze field and laboratory experiments. Focus on statistical analysis for biological scientists. Primary emphasis on analysis of variance, regression, and experimental design. Computer-assisted analysis experience provided.

Prerequisites: a course in basic statistical analysis.

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

With lab. The acquisition, translocation, distribution, and function of the essential inorganic elements in plants. Genetic control of plant nutrition and ecological adaptation to nutritional variables. Diagnosis of plant nutritional disorders. Prerequisites: STOCKSCH 105 and STOCKSCH 108, and either CHEM 110 or 111 or equivalent courses.