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Resources for learning R for ecologists

  • Writer: merineliza
    merineliza
  • Oct 5, 2022
  • 3 min read

I got on my journey to learn R rather randomly. I wanted to find a way to do statistics for my PhD but I wasn't sure which software to choose for the analysis. SPSS was the favourite software for most people in my University. I knew it was paid and wouldn not help me in the long run. SAS was too unheard of and I was too scared to try something few people knew about and had fewer resources online. PAST was another software that seemed easy enough to use and powerful. But customisation was a bit tough in this. That's when I came across R. R had a lot of this recommending it. It was open source, with a lot of online resources, so many new packages being released. But it needed coding, and the only coding I had ever done was some base level HTML that I tried out in the early days of "I want to be a coder" phase. That phase itself stopped when I learned that I had zero talent for coding. I just couldn't think like a coder for some weird reason. I tried using Scratch to learn coding after seeing it on CS50 class by Harvard University in edX. Scratch is super easy to use to learn to code but I couldn't even make something move from point A to B without using huge amounts of code. Even then it showed error and I realised I had bad coding skills. So, when I saw R needed coding skills I was scared to even try. But the lack of good alternatives and a sudden courage from somewhere I thought I'd just try. I installed R and R studio. Now, when you install R studio they have a tutorial on how R works. I took it just to see how R was. There were small exercises in which they taught how to do addition, multiplication, division and basic operaions in R. That seemed simple enough. But that was just the basics. I needed to learn modelling. That seemed so far way. So I got online, googled, read books, looked it up on twitter, and joined multiple online workshops and I think I'm getting the swing of it. I'm by no means an expert in R but I know a lot of good resources to learn them. R itself is not that difficult but there are few resources out there that is helpful for ecologists. Most R books that are for biologists actually work for molecular biology, evolution and many more lab based work. But for field ecologists there are few learning platforms. So I thought i would bring together all the stuff that is useful for me as an ecologist to learn R and do analysis. Not all of them are free, nut they are great resources for understanding R in Ecology.


  1. Google Data Analysis with R Programming (Coursera)




This can be accessed for free on Coursera and is an amasing course if you want to learn how to work in R. This is a part of the Professional Certification Programme but you take each individual course for free. The whole programe is amazing with a basic level of explanation.


2. R for Data Science



This is an amazing book that can be used to learn R mainly visualisation techniques. It has so many great explanations and is easy to understand. The authors have kindly given access to an online copy in their website https://r4ds.had.co.nz/










3. Statistics for Terrified Biologists




This is a great book for learning the basics of statistics that you need. If you don't know the basics no amount of advnaced coding is going to help that much. It teaches p value, normalisation and so on and understanding these are fundamental for doing any statistics.












4. Numerical Ecology by Legendre



This is an amazing book that is designed for ecologists especially for learning the maths behind the numerical ecology. Once you have learned all the basics, this book will help you with narrowing down different analysis techniques that you can use to do you research. It's a bit maths heavy but you can still get the gist of it and uderstand what each analysis is done for, how to understand the results, and how to use them.







5. Numerica Ecology with R



This is similar to the book before but this has R codes for better understanding how to use them in R.













Other resources that I'm still reading: How to be a Quantitative Ecologist by Jason Matthiopoulos.


As an ecologist who knew next to nothing when starting out, I'm sure these resources will help one get a good understanding of ecology with R. One may not immediately understand everything in R. It takes time and effort. Do try out the codes repeatedly until you understand your basics. Best Wishes!




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