About the course
The core of this tutorial is built around the Jupyter Notebooks, an interactive computational environment run in a web browser.
In this particular case we will be using the R programming language for the data exploration/analysis.
What is R?
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 our word for it though – here’s what others have to say
- Why use R? Five reasons - From the ‘Econometrics By Simulation’ blog.
Working with the material
The simplest way to enjoy these materials is to view each lesson online here. In such a case, you could follow along and write your own version of the programs to run with your local R installation.
Working locally
You can also download/fork the whole collections of Notebooks from the GitHub repository. That way you can use your local copy of the materials and follow along the course and make your own modifications/extensions.
If you plan to follow this approach and run the notebooks locally (in your own desktop/laptop) make sure to follow the steps detailed in Setting up R and Jupyter notebooks locally.
Additionally, each of the notebooks have a download button that will allow you to save a local copy of the Jupyter notebook.
Working on the cloud
Some notebooks have been added to a library within Microsoft Azure Notebooks. Whenever you see the cloud action button (see figure above) you can launch the corresponding notebook in Microsoft Azure for free.
Some of the advantages of this method is that you do not need to install any packages/dependencies in your local computer.
Please follow the instructions in running notebooks on the cloud before getting started.