index.Rmd

---
title: "Data Analysis and Visualization in R for Ecologists"
author: François Michonneau & Auriel Fournier (Lesson Maintainers)
site: sandpaper::sandpaper_site
---

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## Try out the alternative version of this lesson!
[A redesigned version of this lesson](https://carpentries-incubator.github.io/R-ecology-lesson-alternative/) 
is currently in beta testing and 
[the Data Carpentry Ecology Curriculum Advisors are looking for feedback](https://carpentries.org/blog/2023/07/r-ecology-alt-beta/)
from Instructors who try teaching it,
with the aim of evaluating whether it should be adopted to replace this lesson in the official Data Carpentry Ecology curriculum.

If you are planning to teach a Data Carpentry Ecology workshop, or this lesson only,
why not try out the alternative version and let the CAC know what you think?

::::::::::::::::::::::::::::::::::::::

Data Carpentry's aim is to teach researchers basic concepts, skills,
and tools for working with data so that they can get more done in less
time, and with less pain. The lessons below were designed for those interested
in working with ecology data in R.

This is an introduction to R designed for participants with no programming
experience. These lessons can be taught in a day (~ 6 hours). They start with
some basic information about R syntax, the RStudio interface, and move through
how to import CSV files, the structure of data frames, how to deal with factors,
how to add/remove rows and columns, how to calculate summary statistics from a
data frame, and a brief introduction to plotting. The last lesson demonstrates
how to work with databases directly from R.

This lesson assumes no prior knowledge of R or RStudio and no programming
experience.

## Contributors

The list of contributors to this lesson is available [in the citation page](https://datacarpentry.org/R-ecology-lesson/CITATION).