PLSCI 7201 - Advanced Statistics and Experimental Design

Fall. 2 credits. Letter grades only.

Prerequisite: undergraduate-level course in statistics. Enrollment limited to: graduate students. Undergraduates must obtain permission of instructor. This module can be taken independently of PLSCI 7202 and PLSCI 7203.

K. Robbins.

This course will provide a comprehensive introduction to experimental designs that are commonly used in plant science and provide participants with the practical coding skills necessary to analyze data from such designs. This basic knowledge will be extended to accommodate high-dimensional data generated by modern ‘omics techniques. This course will provide a foundational introduction of experimental designs and statistical analyses to guide independent research and avoid mistakes that are often made by new scientists. While this course will cover a wide range of topics, it is by no means an exhaustive coverage of experimental design and statistics. Students are strongly encouraged to complement the foundational knowledge learned in this course with classes on advanced statistical methods and/or experimental design.

Outcome 1: Interpret experimental designs that are commonly used in plant science and plant breeding.

Outcome 2: Apply and interpret linear models to account for systematic effects in commonly used experimental designs.

Outcome 3: Extend classical experimental designs and statistical frameworks to challenges and limitations associated with high-dimensional ‘omics data.

Outcome 4: Apply these concepts to meet independent research objectives.