​​Statistics for On-Farm Research (Part 1)

December 2008 | 14 min., 55 sec.
by Paul Esker
University of Wisconsin-Madison


​This six-part presentation provides an introduction to statistical design and analysis for on-farm research. Part 1 covers variability and the principles of statistical design. Part 2 deals with the principles of statistical inference using randomization and using traditional models. Part 3 describes hypothesis tests, the interpretation of results and Bayesian inference. Part 4 offers tips on getting more precise estimates. The concepts of power and blocking are discussed here. Part 5 discusses the extension to more than two treatments by using analysis of variance (ANOVA) and contrasts to answer the appropriate biological questions. And Part 6 covers the analysis of data from multiple locations and years.

About the Presenter

Paul EskerPaul Esker and his research group are focused on increasing the understanding of how plant diseases affect field crops, including corn, soybean, wheat, and alfalfa. Specific interests in his laboratory include the role of decision theory and its application for field crop disease management, how different cropping systems affect plant disease dynamics (including the question of scale), how chemical and biological management tactics may reduce the risk of field crop diseases, and methods to improve diagnosis of field crop diseases. His laboratory also has an extensive international collaboration, with projects currently in Brazil (soybean), Mexico (corn), and Australia (pyrethrum). As the Field Crops Extension Plant Pathologist, Esker's goals include the integration of current research results into sound management recommendations for Wisconsin’s producers through a variety of multimedia approaches, developing training programs for field crop disease diagnosis, and increasing understanding the cost-benefit of using different management tactics for field crop disease control.​

Contact Information:
Email: pde@plantpath.wisc.edu


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