POLSC-UH2211 - Data Analysis: Political Science

Lecture notes for course POLSC-UH2211

Setup

Before the first lecture (required)

Please complete the steps below before coming to the first class.
Nothing else is required.

1. Create a free account on GitHub.

   • You will not be able to change your username later, so choose carefully.
   • Use a permanent email address, so you do not lose access after graduation.

2. Enable GitHub Education.

   • This gives you free access to developer tools used in this course.
   • It also allows you to run R in your browser for about 60 hours per month.
   • This step links your GitHub account to your university email address.
   • If approval is pending, that is fine — you can still follow the first classes.

✅ That’s it. Please do not install anything yet.

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In class: running R in your browser (we will do this together)

During the first lecture, we will set up the working environment together using GitHub Codespaces.

You do not need to install any software on your computer. Everything will run directly in your browser.

Please bring a laptop and make sure you can log in to your GitHub account.

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Optional later: running R on your own computer (advanced)

This step is not required at the beginning of the course.

Once you are comfortable with R and GitHub, you may choose to work locally on your own computer.
We will discuss this option later in the semester.

If you decide to do so, the general steps are:

1. Install Git (e.g., GitHub Desktop)
2. Install R
3. Install the IDE of your choice (see pros and cons below):
   • RStudio
   • VS Code
   • Positron (recommended)
4. Clone this repository to your computer using GitHub Desktop
5. Open the repository folder in your IDE of choice and start working!

Please come to office hours or talk to me after class if you need help with this step.

IDE options: pros and cons

IDE	Pros	Cons	Who for?
RStudio	• First-class support for R • Designed specifically for data analysis • Many students may have used it before • Very simple setup	• Interface feels a bit dated • Only supports R (and a bit of Python) • No AI features	People who have used RStudio before
Visual Studio Code	• Matches GitHub Codespaces exactly • Industry standard across many fields; support all languages (R, Python, etc.) • Excellent AI support	• R support is less polished and needs some initial configuration (follow tutorial here)	People who want to replicate the Codespaces experience exactly
Positron	Built on VS Code, so inherits most same strengths (very similar interface)• Cleaner R experience than VS Code • Better AI support for data analysis	• Newer, so less polished than VS Code	My recommendation for most students