Course information

Course title
R without Fear: Applied R for Biologists
University / Organization
Transmitting Science
Academic level
Both Msc and PhD
Course director
Course lecturer(s)
Dr Oriol Verdeny-Vilalta (Ynsect, France)
Course aim
Course overview In this course the students will learn how to use R to solve the most common tasks faced by the statistical practitioner. After reviewing basic R syntax, we will cover practical issues in statistical analysis: Data manipulation, data analysis using regression methods –from simple linear regression to generalized linear models– and data visualization. In this learn-by-doing course we will start each section with an introduction to the statistical concepts that we will study. Then, the students will start practicing the newly acquired concepts working in the R environment, either by examining code examples or by solving exercises. The course directed towards students who have a base experience in R and statistics but wish to develop or improve their skills, but it is not targeted to participants with extensive or none experience in R. By the end of the course the students will be able to use R to undertake most of their own statistical analysis with proficiency.
Course contents / programme
Program Monday, June 4th, 2018. Introduction to R and RStudio. Brief introduction to R. Review of R basics. The RStudio environment. Reproducible research: R scripts and R markdown. Data manipulation I. Read your data: Local vs. remote location. Tuesday, June 5th, 2018. Data manipulation II. Tidy your data. Manage your data. R Pipelines. Summarize your data. Wednesday, June 6th, 2018. Regression models I. Linear regression. Multiple linear regression. Thursday, June 7th, 2018. Regression models II. ANOVA. Generalized linear model. Non-linear model. Friday, June 8th, 2018. Data visualization with ggplot2. Grammar of graphics. The ggplot. Basic visualizations (regressions, bar plots, error bars…). Customize the ggplot.
Required Knowledge and preparation
Teaching methods
Course type
Consecutive days
Online course
Duration (net days)
June 4th-8th, 2018
Course fee
Direct e-mail to register
Paper submission required?
Logo of institution
front approval