Rapid reporting for analysts: An Introduction to R programming through to reporting in three days
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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: Graphics
- Introduction to a versatile approach to achieve impressive graphics in R with ggplot.
- Creation of different plot types: histograms, scatter, density, box plots.
- Working examples of how alter the design, including scales, axes and legends.
- Adding the finishing touches with colours, themes, additional information.
Day 3: Automated Reporting
- Rmarkdown: Creating documents using Markdown
- knitr: Running dynamic R code
- Automate: Automate documents and apps
- LaTeX: A brief introduction to latex for additional styling
- 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 Rmarkdown.
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.