This is designed to be a self-directed study session where you work through the material at your own pace. It is designed to give IT Support staff an idea of what R can do along with an outline of the eco-system of tools that exist alongside it.
- It was delivered to a group of IT support staff and Research Software Engineers at University of Manchester on Friday 20th May 2016
The introductory presentation that goes with this material can be found at http://mikecroucher.github.io/R_awareness/#/
R is a free, open-source programming language that has very strong support for statistics. It was originally developed as an open source implementation of the S Programming language. It is used extensively in research and industry for areas such as data analysis, statistics, machine learning, bioinformatics, simulation, linguistics and much more.
With over 8000 freely available add-on packages that provide extensive additional functionality, R will probably have something that can help your research.
Don't just take my word for it though -- here's what others have to say
- Why use R? Five reasons - From the 'Econometrics By Simulation' blog
- The Popularity of Data Analysis Software - Compares R with SPSS, SAS, MATLAB etc
The material assumes that you are starting with a clean version of Windows (in a VM perhaps) that has nothing installed.
- Section 1 - Install several versions of R and learn some basic commands
- Section 2 - The Importance of packages
- Section 3 - R Studio : A popular user interface for R
- Section 4 - Jupyter Notebook
- Section 5 - R in the cloud: SageMathCloud
- Section 6 - Revolution R Open - A faster R from Microsoft
- Section 7 - How R interacts with other applications
This work is licensed under CC-BY 3.0.
- Human readable description of the license - https://creativecommons.org/licenses/by/3.0/
- Legal text of the license - https://raw.githubusercontent.com/mikecroucher/R_awareness/master/license.txt