Online live sessions on Monday from 13:00 to 16:30 and 17:30 to 20:00 (Madrid time zone) and from Tuesday to Friday from 14:00 to 16:30 and 17:30 to 20:00 (Madrid time zone). The instructor will be available for answering questions from 13:00 to 14:00 and from 20:00 to 21:00.
The aim of this course is to give an introduction to R addressed to people that have never used R.
By the end of the course, students will be able to:
- Understand R syntax and navigate RStudio software sufficiently to author (or identify, evaluate, and apply) code specific to their individual research fields
- Identify and apply code and workflow strategies that promote reproducibility, efficiency, and collaboration
- Confidently anticipate and troubleshoot common errors and gain help from the R user community
Instruction via lecture and live-coding will be followed by exercises and multichoice questions to practice and evaluate skills. Students will have the option to perform exercises with class data or their own data.
All participants must have a computer (Windows, Macintosh) with current versions of R and R Studio pre-installed. If you have any problem installing them, please contact the course coordinator.
Webcam and headphones are strongly recommended, as well as a good internet connection.
Click here to see the full Program
Orientation to RStudio software and R language
- Manipulate basic data structures: vectors, matrices, dataframes, lists
- Install code packages and use functions
- Manage working directory and environment
- Establish good coding style practices
Read and inspect data
- Import tabular, spatial, and other data formats
- Perform quick data inspection via summary functions
- Perform quick data inspections via plot functions
- Identify and handle missing values
- Subset data by multiple methods
- Create new variables
- Group and summarize data
- Join two datasets based on common ID value
- Export data to common formats
Data visualization (ggplot2)
- Create common graphs (scatterplot, boxplot, bar graph, time series plot)
- Customize graph text and aesthetics
- Export graphs to common image formats
Efficiency and reproducibility
- Identify common strategies to manage projects in R
- Use R Markdown to interweave code and text
- Find and evaluate R packages and help resources
- Write your own functions to perform common tasks