Introduction to the R language
This set of lectures/practicals are part of the University of Luxembourg Bachelor of Life Sciences referred as BASV53.
Introduction to
Prerequisites
You can ensure that your laptop is ready, and browse both the lectures and practicals.
Description
The course will be structured around computer practical’s and will cover the following issues :
- Introduction to programming
- Basic concepts of algorithm building
- language
- Focus on the Integrated Development Editor Rstudio
- Data wrangling
- Import
- Tidy
- Transform
- Visualise
- Communicate
- Descriptive statistics with R
- variance, mean, median and distribution descriptors
Tidyverse
Enhance base functions with the tidyverse. Adopt Hadley Wickham philosophy, take each step of data science and simplify the tools. Keeping what make them helpful and removing inconsistent and historic behaviors. Tidy data starts with rectangle data, so a table of columns of the same length. Then, each column is an independent variable and rows are observations. His recommended workflow is depicted below from his must-read book R for data science
H. Wickham - R for data science, licence CC
Learning Outcomes
The final aim is to provide a methodology and framework to work as a data scientist. This encompasses everything from importing raw data to final communication as described by Hadley Wickham. This course should provide students with enough content to empower them on the road to be autonomous in the process data wrangling. Biostatistics and modelling is not part of this course, and will be taught in the second and third year of the bachelor.