Welcome to the tidyverse! This course is the first part of a two-part series about learning to tell stories with data using a scientific workflow and analytic tools based on the R system.
In this course there is a focus on the reflection, collection and preparation stages of the data science process. We learn about importing data presented in almost any format into R, a standard concept of tidy data and how to transform messy data sets into tidy ones, and how to explore a data set, using techniques such as visualisation and other tools, so that it is ready for analysis, using a hands-on approach via case-studies.
Aims, Objectives and Intended Learning Outcomes
In this two-day course we learn about the data science workflow:
Reflection – Collection – Preparation – Analysis – Reporting
and how the tidyverse, a collection of R packages specifically developed for contemporary data science, assists at each stage of the flow in a standardised, coherent and reproducible way.
Familiarity with R and RStudio