Statistical Design and Analysis of Agricultural Experiments Using R

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This course provides researchers with the knowledge and skills to be able to design and analyze agronomic experiments using the R programming language. Through a combination of lecture, group exercises, and hands-on activities, participants will learn the designs commonly used in agricultural research, analysis of variance, and correlation and regression analysis. This course is intended for researchers in agricultural and biological sciences, and is foundational for learning more advanced statistical techniques.

Course Objectives

  • Understand when to use different experimental designs and how randomization and layouts are generated
  • Understand and learn how to perform mean comparisons and analysis of variance
  • Understand and learn how to use data transformations
  • Understand how to handle missing data
  • Understand how to study relationships between variables using correlation and linear regression

Course Content

  • Basic statistics
  • Principles of experimental design
  • Experimental designs commonly used in agricultural experiments
  • Analysis of variance and mean comparison
  • Partitioning sum of squares
  • Data transformation
  • Missing data
  • Simple correlation and linear regression analysis

Prerequisites

BIOM 203: R Programming or equivalent

Notes

  1. Applicants will be notified thru email if they are accepted or not.
  2. Participants must bring their own laptop with Windows Operating System.