R course for beginners

Research data are an essential part of most research projects. Processing, analyzing, and visualizing the data collected or generated is very important so that methods are reproducible and presented with good aesthetics. R is an open-source software that can handle large datasets and run complex simulations. Its popularity and need have increased rapidly and though proficiency in R is often desirable, there are limited learning options within high education programs. 
This course is an introduction to programming with the open-source R software. In this course we will walk you through the basics programming using R language for processing biological data, though the principles we will use are also applicable to other fields such as social sciences. We introduce you to R syntax, R packages, RStudio interface, and different data types, so that you learn how to import and perform simple operations on datasets. Further, we will demonstrate how to do basic pre-processing, operations and statistics on your datasets, and how to plot the data. This course will highlight the benefits of using R for analyzing, visualizing, and sharing research data. At the end of the course, you will receive a signed certificate and will be able to independently perform basic operations in R.

Everyone is welcome, regardless of their academic level. You don´t need any programming background to join the course but are expected to bring your own laptop with R and RStudio software installed.  

Course details:

The course will run for 2 weeks, starting in week 35.

Classes will be on Tuesdays and Thursdays between 13:00 and 15:30 (we leave additional 30 min at the end for questions) at the Fisheries Building room D-110

At the end of each class, the attendees are expected to store all notes and analysis in an R script.

BFE students/employees will be prioritized.

For more information contact ana.s.aniceto@uit.no

To avoid registration issues, please contact one of the organizers once you sign up to make sure you are on the list.

Session 1: Introduction to Rstudio and R language

• Going through Rstudio interface
• Setting work directory
• R data types (vector, data.frame, matrix, list,…)
• Syntax, and how to create datasets
• Simple operations
• Installing and loading packages
• Basic functions and packages
• Finding information on functions

Session 2: Importing and operation on datasets

• Import datasets in Rstudio
• Data structure (characters, numeric, …)
• Operation on datasets (filter, sort, summarize, “for” loop, etc.)

Session 3: Visualizing data

• Different graphics
• Base plots
• Spatial data, displaying maps
• Introduction to ggplot

Session 4: To go further

• Using Rmarkdown for reports, and power points
• Introduction to tidyverse
• SjPlot for statistics summary (tabmodel)
• GitHub