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  • For general concepts, check out these Mod U videos on causal inference from the Social Science Research Institute at Duke. They are great for brushing up on concepts or expanding your understanding.  
  • Also, Duke’s Center for Data and Visualization Sciences is an excellent resource for students, faculty, and staff alike. You can set up an appointment with one of their consultants, especially if you need some tips for navigating through R.
  • Many in the Nunn lab use Bayesian statistical methods.  For a great introduction - which covers core statistical concepts in an innovative way - check out Richard McElreath's "Statistical Rethinking" book, videos, and R-package.  It is challenging, but also feasible to work through.
  • Through your affiliation with Duke, you also have access to Coursera online courses, such as those in the their Statistics Specialization.
  • For more advanced training in phylogenetic comparative methods, see here.
  • For more advanced training in meta-analysis, see hereMost people in the lab are using R.  This book is a great introduction to R and the tidyverse collection of R packages for data science.

If you have more specific questions about statistical methods, be sure to spend time working in the Nunn lab, as others who are in the lab would be happy to take a look at your project and answer questions. Alternatively, you can always set up a meeting with Charlie or another Nunn lab member to have a conversation about methods.