Course Introduction

Prerequisites

Participants must be able to use a laptop/computer capable of running recent RStudio. See below for the RStudio Installation section.

Teachers

Szymon M. Kiełbasa (s.m.kielbasa@lumc.nl)
Ramin Monajemi (r.monajemi@lumc.nl)
Mo Arkani (m.arkani@lumc.nl)

What we teach

R is an open-source, free environment/language for statistical computing and graphics. It provides a large repository of statistical analysis methods.

The goal of the course is to teach students how the R language, extended by tidyverse package, can be used to build a report with a simple statistical analysis of data provided in a table. The course assumes no prior programming knowledge.

NOTE: This is not a statistics course! We do not teach statistics; we teach how to write simple programs in the R language. Elementary statistics knowledge is necessary to understand examples.

After the course you will:

Understand and write (tidyverse-based) R code.
Know where to look for R methods to perform statistical analyses of your own data.
Generate reproducible reports from your own data in HTML, PDF or DOC formats.

We will cover the following topics:

R expressions.
R data objects: vectors, data frames (tibbles), lists, (matrices).
R Markdown for building reproducible reports.
Data manipulation: filtering, sorting, summarising of a table; joining/merging multiple tables (with tidyverse/dplyr and tidyverse/tidyr).
Visualisation: scatter plots, histograms, boxplots (with tidyverse/ggplot2).
R packages: installation and usage.

Course structure

The course is divided in half-day sessions.
The teachers are available for chatting online during all teaching slots.
At the beginning of the week before the course the teachers might be contacted to help with R and RStudio installation problems (see below).

All sessions: practicing

The course is given in an online plenary room. Each session is split into a few small topics and each topic is introduced as follows:

A short online (live video) lecture for introduction/demonstration.
A self-study practice session (with primary exercises end extra exercises) with chat interactions.
(Only when needed) A short chat question and live video answers session.

The students are asked to type on their keyboards the commands being presented and observe effects (avoid copy-paste; own typing is important in order to learn how to respond to mistakes/errors).

The last session: practicing followed by self study assignment

A self study assignment (SSA) will be offered during the last session. A set of tasks will be provided to be solved individually without help of the teachers or other persons. At the end there will be a general discussion with chat questions and live video answers.

The overall SSA goal is to prepare an R Markdown document reporting an analysis of a dataset. You will be asked to carry out the following steps:

Create an RStudio project, knit an R Markdown document.
Read a provided table.
Show some filtered/summarized content of the table.
Produce some plots of the data.

Installation

Before the course prepare your computer.
NOTE: Resolving installation problems during the course may be impossible, therefore please follow the steps below a week before the start of the course. In case of failure, please inform the teachers. In some situations intervention of the administrator of your computer might be necessary.

Install R: Go to the R Project for Statistical Computing (https://www.r-project.org/) and follow the download and installation instructions.
Install RStudio: Go to the RStudio download page (https://www.rstudio.com/products/rstudio/download/#download), select a version of RStudio appropriate for your laptop, download it and then install. Please check whether you can start RStudio.

Some additional packages are needed for the course. During the course the participants will learn how to install packages but this process occasionally fails (because e.g.: additional steps are needed in a particular operating system, or there is lack of permissions to access some system directories, or other software is too old, …).

Install Rtools (Windows only!): During installation of some packages you may encounter the following error Rtools is required to build R packages but is not currently installed. If that is the case, follow the Rtools installation (https://cran.rstudio.com/bin/windows/Rtools/).
Install tidyverse package: Start RStudio. Go to menu Tools/Install Packages... In the field Packages select tidyverse. Press Install. (Now, a lot of messages will be shown in the Console window - wait till it finishes). In the Console window type library( tidyverse ) and press Enter. Some messages might be displayed but when there is no error the installation is completed.
Install packages needed for R Markdown: Start RStudio. Go to menu File/New File/R markdown.... A New R Markdown window is displayed. Press OK. Now, in case of missing R Markdown packages, you will be asked to install them. Finally, you will see an editor window with Untitled1 header. Put the cursor in that window, then click Knit. Some messages might be displayed but when later a window with some text and a plot is shown the installation is completed.

During the course applications in multiple windows will be used. For better experience we advice a setup with two monitors (e.g. laptop and an external monitor).

R Introduction →