STATISTICS FOR ECOLOGY AND CONSERVATION BIOLOGY March 11-22, 2019 Gain in-depth knowledge of analysis techniques for cutting-edge ecological research, employing R: classical regression models; mixed models; generalized linear models; how to deal with the limitations of real datasets; and conservation-specific approaches. Participants learn how to choose appropriate analyses for different research questions, and about the assumptions underlying each model. Through the lectures and hands-on exercises participants learn how to explore their data, perform a range of analyses, understand fitted models, and clearly explain their results. By the end of the course, participants will be able to conduct sophisticated statistical analyses, critically evaluate statistics-based material in current research literature, and deal with the limitations of real datasets in the context of conservation science. Early course material and pre-course work focuses on teaching the basics of R and all work during the program is conducted in R including data manipulation and graph creation. The course does not require previous experience in R.
All The Smithsonian-Mason School of Conservation courses are either 1- or 2-week intensive residential courses hosted in our sustainably-built Academic Center on the grounds of SCBI in Front Royal Virginia. All courses offer continuing education credits (CEUs) and some can be taken for graduate credit. Limited scholarships are available for eligible applicants for some programs. Visit our website (http://SMConservation.gmu.edu) for more details about each course, course costs, and credits earned. Additional courses for late 2019 will be added soon. ADDITIONAL UPCOMING COURSES: AniMove: Statistics for Animal Tracking Data (February 11-15, 2019: Apply before November 16!) Communication and Facilitation Skills for Conservation Managers (April 8-12, 2019) Practical Zoo Nutrition Management (May 6-10, 2019) Camera Trapping Study Design and Data Analysis for Occupancy and Density Estimation (June 10-21, 2019) Essentials of Spatial Ecology: GIS Analysis in R, QGIS and Google Earth Engine (September 16-20, 2019)
