ST524 - Statistics In Plant Science
- Prerequisites: ST512
- Term & Frequency: Every other fall
- Student Audience: Graduate students in Crop Science, Horticulture, Forestry, and related fields
- Credit: 3 credits
- Recent Texts: None required, but several recommended
- Recent Instructors: Kevin Gross
- Background and Goals: Graduate students in the plant sciences have frequent need to understand statistics, including experiment design, for their own research, in reviewing literature, and in evaluating presentations in seminars and professional meetings. Although the focus will be on proper application of statistical tools, this requires both sufficient understanding of key theoretical underpinnings and a strong intuitive feel for the material, which this course provides. Computations are nowadays mostly done by packaged programs; this course focuses on what the experimenter needs to know in instructing the packaged program to do the correct computations.
- Content: Explores statistical techniques used in field, greenhouse, and laboratory experiments with plant material. Building on the fundamental ideas of randomization, replication and error reduction. Determining sources of variation and degrees of freedom for a variety of standard and non-standard designs; fixed versus random factors; expected mean squares. Blocking, including use of incomplete blocks. Analysis of covariance. Introduction to use of confounding and fractional replicates with factorial treatment designs. Proper use of SAS; annotated SAS output distributed and discussed.
- Alternatives: St711
- Subsequent Courses: None
S1 2017 Sections:
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