Experimental Design and Applied Statistics in Agroecosystem Science

Abstract

In this course, different experimental designs will be discussed and various statistical tools will be applied to research questions in agroecosystem sciences, ranging from simple t-tests to multi-factorial analyses (ANOVA, Principal Component Analysis, Cluster Analysis) and nonlinear multiple regressions as well as basic time series statistics.

Objective

Students will know various statistical analyses and their application to science problems in their study area as well as a wide range of experimental design options used in environmental and agricultural sciences. They will practice to use statistical software packages (R), understand pros and cons of various design and statistics, and be able to statistically evaluate their own results as well as those of published studies. Students will know about scientific ethics and consequences of scientific misconduct.

Content

In this course, the basics of the scientific method and experimental design (e.g., hypotheses, pseudo-replications, proper controls), but also ethics of scientific work will be discussed. Different experimental designs will be developed based on research questions the students are familiar with, ranging from random to nested, multi-factorial designs. Statistical tools will be applied to research questions in agroecosystem sciences, ranging from simple t-tests to multi-factorial co-variance analyses and multiple regressions as well as geostatistics. Published literature will be examined for proper design and statistics to answer the stated objectives, and will serve as starting point for further discussions. Thus, students will learn to apply the new knowledge to research questions in their study area, to critically review published literature and present their opinion to their peers.

Resources