Introduction to R

Introduction to data management and data analysis with R and RStudio.

Outline

The course is grouped into (potentially overlapping) sections which do not necessarily need to correspond to workshop days.
The sections are:

1. Getting started

Setting up R and RStudio and getting familiar with RStudio as an environment
Basic R syntax and common language features such as the included help system
Essential data types and data structures
Familiarization with example datasets used throughout the course
Using Quarto as the environment for code examples and exercises

2. Exploratory data analysis

Creating and manipulating tabular data with the tidyverse
Preparing for typical data cleaning tasks
Data visualization basics using ggplot2
Descriptive statistics to understand one’s data
Assess data integrity
Paving the way for publication-ready tables and visualizations using extension packages

3. Statistical analysis

Basic hypothesis testing for common research questions

Prerequisites

Ideally R and RStudio are already installed at the start of the course. See these instructions for example.

If a local setup is not feasible, consider using an online service such as Posit Cloud (see below).

How to use this repository

Depending on your setup, you can either work with these materials locally on your own computer or in the browser on a cloud service, Posit Cloud.

Installing the required packages is part of the course, but if you want to be safe and install them in advance (e.g. due to technical issues like an unstable internet connection) follow these instructions depending on your preferences / needs and afterwards refer to scripts/install-packages.R and run the commands to install the R packages.