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2018 Advanced STATS workshop announcements

时间:2018-02-11  来源:科学传播与培训部  浏览次数:   作者:刘景欣     打印  字体: 关闭

  Title:  2018 Advanced Statistics Workshop, XTBG 

  Venue: Bubeng Station, Xishuangbanna Tropical Botanical Garden (XTBG), Chinese Academy of Sciences 

  Dates:  workshop will be held 25 – 31 March 2018 

  Registration deadline application will be closed at 10 March 2018 

  Organiser: Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences 

  Sponsors: Centre for Integrative Conservation and Science Communication and Training Department of the Xishuangbanna Tropical Botanical Garden, CAS 

  Registration fee600 RMB/person (including lecture room, materials, transport between XTBG and Bubeng station, allowance for instructor and other staffs; not including  transportation between your organization and XTBG, hotel and food during the workshop etc.) 

  About the workshopThis advanced workshop aims at introducing students to linear modelling methods that are commonly used in Ecology today. The workshop consists of a series of modules that build on each other towards more complex linear models, starting from simple linear models, through generalised linear models, to mixed effects models and ending with linear models with generalised least squares and phylogenetically correlated data. We expect participants should be competent at using these methods after the workshop and understanding when they are appropriate to use. 

  Requirements for applicants: 1). Experience with conducting analyses in R;  2). Familiar with linear models and generalised linear models. 

  Workshop outline 

  Module 1: Revision of linear models and generalised linear models 

  Go over the lm() and glm() functions, discuss assumptions of the models, run diagnostics, and make predictions with the models. 

  Module 2: Dealing with grouped data: Linear mixed models 

  Go over the concepts of grouped data and how to deal with it using linear mixed models (LMM). 

  Module 3: Dealing with grouped data: generalized linear mixed models 

  Extend the LMM analysis to the GLMM case. Main goal here is to imprint the differences between lm, glm, lmm and glmm. 

  Module 4: Dealing with non-independent data that cannot be grouped: generalized least squares 

  Deal with non-independence between data points when the data cannot be easily grouped. Also cover the problem using spatial-dependence between data points. 

  Module 5: Dealing with phylogenetically correlated data 

  Comparative data analyses routinely correct for autocorrelation among species’ data caused by shared evolutionary history between the species. Common methods to deal with this problem and some of the considerations when dealing with autocorrelation will be covered. 

  Module 6: Exercise and revision 

  Assuming timeous completion of the previous modules, on the final day applicants will be given several problems for which they will need to figure out appropriate analyses to deal with the questions and data provided. 

  Student number: not more than 20 

  Instructor: Professor Kyle Tomlinson, PI of Community Ecology and Conservation Group of XTBG, working on landscape conservation, forest ecology, savanna ecology, and functional trait diversity. Kyle is a very good and experienced statistic instructor and has been invited to run statistic workshops during ATBC-Asia chapter annual meetings since 2014, and during Advanced Fieldcourse in Ecology and Conservaton (XTBG’s annual international training program) since 2013. 

  Please go to to register 


  If you have any questions about the workshop, please email,  and/or