Introduction to R and analytic Programming
Welcome!
Introduction
Transitioning from manual tools (e.g. Excel & Prism) to programming-based workflows in R.
Handling data - be specific!
Directories
Reproducibility and automation
Chapter 1: Getting Started in R and RStudio
R as a programming language
Installing R and RStudio
Navigating RStudio
Projects
Using R
Hello World
Optional Exercise: Write your
first
second script
Next Chapter
Chapter 2: Data Types and Structures
Data Types
Data Structures
Importing and saving files in R
Chapter 3: Basic Programming
Assigning variables
Conditional statements
Loops
Writing a function
Chapter 4: Data Manipulation with
tidyverse
Why use tidyverse
Filtering rows and columns
Adding a column using
mutate()
group_by()
and
summarize()
Pivot
Hopefully it is clear why
tidyverse
is a useful tool.
Chapter 5: Data Visualisation with
ggplot2
Basics of ggplot2
Scatterplot
Boxplot
Column/bar graph
Summary
Chapter 6: Data Visualisation with
ggplot2
2
Adjusting theme elements
Annotating the plot
facet_wrap() and Group
Saving plots
Some final hints
Chapter 7: Statistical Analysis
Descriptive statistics
Chapter 8: Reproducible Reports with RMarkdown
Conclusions
Return to the analysis page!
See The Source Code
Introduction to R and analytic Programming
Conclusions
Content coming soon!
