Welcome to the tutorials of our Ecological field research course!

Course code

GEO2-2439

Prologue

This Quarto website has been created to provide you with a single, searchable platform containing all the tutorials and R code used during our ecological field research course. We hope you will find it useful for learning data science in R and working on your course assignments.

The effectiveness of these tutorials lies in their practical approach. Instead of quickly scrolling down our tutorials and simply reading R code, we encourage you to actively use it and to take the time to understand what each function does. Even if you find learning R difficult at first, don’t give up and just keep learning at the pace that suits you. Learning R is exactly like learning a new language. At first, you can only write and speak short, simple sentences, but with regular practice, you will soon be able to write and understand the language fluently. The best way to learn R is by practicing it and reusing the same commands over and over again.

Now get ready to improve your data science skills. Let’s get started!

How to use our tutorials to learn R

Each tutorial is designed as a step-by-step guide to performing specific tasks that are very commonly used in data science. As well as providing the R code, we take care to explain what we want to do and what each function does. By default, the R code is hidden from you, so you can try writing the R code yourself (it is the best way to learn R). We always tell you which function you need to use to perform each task. Use the R help pages to find out more about these functions. If you get stuck and want to see how the R code should be written, just click on “Show me the R code”. If you have never used R before and want to see the whole R code from the beginning, you can click on “Show All Code” in the Code menu at the top right of each tutorial page.

R for Data Science

Our tutorials rely on the R for Data Science book (second edition) written by Hadley Wickham, Mine Cetinkaya-Rundel, Garrett Grolemund, and many other contributors. To freely access the content of this book, just click on its cover. Thank you to the authors of this book for creating such a gold mine of infoRmation. Due to the time constraints of our course, it is unfortunately not possible to go through all of the techniques and R code described in this data science book, but we strongly encourage you to explore its content and continue to learn new skills.

--- title: "Welcome to the tutorials of our Ecological field research course!" --- ## Course code GEO2-2439 ## Prologue This [Quarto](https://quarto.org/) website has been created to provide you with a single, searchable platform containing all the tutorials and R code used during our ecological field research course. We hope you will find it useful for learning data science in R and working on your course assignments. The effectiveness of these tutorials lies in their practical approach. Instead of quickly scrolling down our tutorials and simply reading R code, we encourage you to [actively use it]{.underline} and to [take the time]{.underline} to understand what each function does. Even if you find learning R difficult at first, don't give up and just keep learning at the pace that suits you. Learning R is exactly like learning a new language. At first, you can only write and speak short, simple sentences, but with regular practice, you will soon be able to write and understand the language fluently. The best way to learn R is by practicing it and reusing the same commands over and over again. Now get ready to improve your data science skills. Let's get started! ## How to use our tutorials to learn R Each tutorial is designed as a step-by-step guide to performing specific tasks that are very commonly used in data science. As well as providing the R code, we take care to explain what we want to do and what each function does. By default, the R code is hidden from you, so you can try writing the R code yourself (it is the best way to learn R). We always tell you which function you need to use to perform each task. Use the R help pages to find out more about these functions. If you get stuck and want to see how the R code should be written, just click on "Show me the R code". If you have never used R before and want to see the whole R code from the beginning, you can click on "Show All Code" in the Code menu at the top right of each tutorial page. ## R for Data Science Our tutorials rely on the **R for Data Science** book (second edition) written by Hadley Wickham, Mine Cetinkaya-Rundel, Garrett Grolemund, and many other contributors. To freely access the content of this book, just click on its cover. Thank you to the authors of this book for creating such a gold mine of infoRmation. Due to the time constraints of our course, it is unfortunately not possible to go through all of the techniques and R code described in this data science book, but we strongly encourage you to explore its content and continue to learn new skills. [![](Cover_R_for_Data_Science.jpg){fig-align="center" width="200"}](https://r4ds.hadley.nz/)