The type of the event is Short Course.
The title of the event is Introduction to the analysis of messy data.
The proposed event is a full day course (8 hours long with 3 breaks), Monday, August 15 preferred (Tuesday, August 16 less preferred).
Dr. Peter Solymos \ Alberta Biodiversity Monitoring Institute and the Boreal Avian Modelling Project \ Department of Biological Sciences, CW 405, Biological Sciences Building \ University of Alberta, Edmonton, Alberta, T6G 2E9, Canada \ Phone: (00-1) 780-492-8534 \ Fax: (00-1) 780-492-7635 \ E-mail: solymos@ualberta.ca \ Web: http://peter.solymos.org
Number of participants: minimum 10, maximum 30.
The instructor is not charging fees for teaching the course.
This course is aimed towards ornithologists analyzing field observations, who are often faced by data heterogeneities due to field sampling protocols changing from one project to another, or through time over the lifespan of projects. Such heterogeneities can bias analyses when data sets are integrated inadequately (Matsuoka et al. 2012, Auk 129:268--282; Solymos et al. 2013, Methods in Ecology and Evolution 4:1047--1058), or can lead to information loss when filtered and standardized to common standards (Matsuoka et al. 2014, Condor 116:599--608). Accounting for these issues is still important for estimating status and trend for bird species and communities, thus better informing large scale conservation and management (Barker et al. 2015, Wildlife Society Bulletin 39:480--487).
Analysts of big and messy data sets need to feel comfortable with manipulating the data, need a full understanding the mechanics of the models being used (i.e. critically interpreting the results and acknowledging assumptions and limitations), and should be able to make informed choices when faced with methodological challenges (Solymos et al. 2012, Environmetrics 23:197--205; Solymos & Lele in press, Methods in Ecology and Evolution).
The course emphasizes critical thinking and active learning. Participants will be asked to take part in the analysis: first hand analytics experience from start to finish. We will use publicly available data sets to demonstrate the manipulation and analysis of large scale and often messy data sets. We will use examples and case studies from the peer-reviewed literature, including the references cited in this proposal. We will teach the use of the following freely available and open-source R packages:
mefa4
for manipulating large data, ResourceSelection
package for presence-only data.detect
for time-removal sampling, distance sampling, single visit based N-mixture and occupancy models,unmarked
for multiple-visit based occupancy and abundance models.The expected outcome of the course is a solid foundation for further professional development via increased confidence in applying these methods for field observations.
Dr. Solymos is a statistical ecologist and author of several R packages (dclone, detect, ResourceSelection, mefa4, vegan) with extensive teaching experience in classroom settings and consulting experience including NGOs, governments, academic and industry sectors.
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