Course Outline
Day 1: Introduction to R
- Introduction to R: A brief overview of the R environment including the R working
directory, creating/using scripts, saving data and results.
- Data entry: A description of how to import and export data from R.
- Data analysis: Learn quick efficient methods to gain insights from data using {dplyr}.
- Summary statistics: Calculating means, variance and other useful data summaries.
Day 2: Advanced Graphics with R
- Introduction to a versatile approach to achieve impressive graphics in R with {ggplot2}.
- Creation of different plot types: histograms, scatter, density, box plots.
- Working examples of how to alter the design, including scales, axes and legends.
- Adding the finishing touches with colours, themes, additional information.
Day 3: Reporting with R Markdown
- R Markdown: Creating documents using Markdown
- {knitr}: Running dynamic R code
- {kableExtra} & {DT}: Embedding tabular data into output documents
- {bookdown}: Writing books and long-form reports with R Markdown
- {flexdashboard}: Creating interactive dashboards
- Parameterised reports: Creating flexible reports
- Widgets: Exploring interactive HTML widgets
Learning Outcomes
By the end of the course participants will be able to…
- Import and export their own data from spreadsheets and other data storages to R.
- Manipulate data in ways such that they can efficiently analyse data.
- Be able to efficiently plot their own data in eye catching ways within seconds.
- Be able to customise their graphs with colour schemes, themes, fonts and grid layouts.
- Learn to build automated reports including data, text and graphics using R Markdown.
Prior Knowledge
No prior programming knowledge of any kind is assumed. This course is suitable for all fields of work. Previous attendees include biologists, statisticians, accountants, engineers & students, i.e., anyone who uses a spreadsheet! Participants should bring a laptop.
