Statistics For Ecologists Master Courses Save

Statistics for ecologists

You will find here the material for a course I give every year to Master students at University of Montpellier.

Topics covered

• Distributions (22-59) and likelihoods (60-84)
• Hypothesis testing (85-106) and multimodel inference (107-125)
• Introduction to Bayesian inference (126-179)
• Generalized Linear Models GLMs (180-244)
• Generalized Additive Models GAMs (245-247)
• Mixed Effect GLMMs and GAMMs (248-306)

How to use this repo?

• The PDF of the lecture slides can be downloaded here
• The practicals are here and the solutions there
• The videos are also available (in French) on Youtube here:
  • Lecture 1 covering slides 1-140 download here
  • Lecture 2 covering slides 140-180 download here
  • Lecture 3 covering slides 180-245 download here
  • Lecture 4 covering slides 245-305 download here
• The R codes I use in the lectures and the practicals are also provided here and there respectively
• To download the whole repo on your computer, click on the Code green button at the top right of the page and choose Download ZIP
• Alternatively, click on same green button to create a copy of the repo within your own GitHub account (clone)

Problem

If you spot a typo or an error, find a bug, or have trouble running the code, please file an issue or get back to me.

Licence / License

This work is licensed under a Creative Commons Attribution 4.0 International License

To-do list

• Besides books, add a few relevant papers and pointers to videos
  • On GLMs, O'Hara's paper https://doi.org/10.5735/086.046.0205
  • On GLMMs, Bolker's TREE paper https://doi.org/10.1016/j.tree.2008.10.008 and FAQ https://bbolker.github.io/mixedmodels-misc/glmmFAQ.html
  • On Bayesian analyses, McElreath lectures and videos https://github.com/rmcelreath/statrethinking_winter2019
• Include more ecological examples, and maybe use just one or two examples throughout
• Consider an example mixing continuous and discrete explanatory variables
• Illustrate how to report results
  • Have a look to recent papers in the journal you’re targeting
  • Check out Zuur's books
  • Read http://bit.ly/2v9dAI8
• Introduce the tidyverse. Or refer to some material I wrote https://github.com/oliviergimenez/intro_tidyverse