Quantitative Analysis for IA Practitioners

IAFF 6501

Welcome!

Professor Teitelbaum ejt@gwu.edu
Office Hours: Tuesdays, 3:00-5:00 p.m.
Monroe Hall Rm 411 or online
Go to my calendly page to sign up for a slot

Why Take this Course?

International Affairs is changing!
Data is everywhere and it is changing the way government works
You will be a better consumer of data and research
You can be a “bridge builder” between traditional analysts and data scientists on your team

Data Informed Dipomacy

Data is a critical instrument of diplomacy. When our workforce has data at their fingertips they are better prepared to engage diplomatically, manage effectively, and lead globally.

Secretary of State Anthony Blinken, 2022¹

Open Goverment Data Act (2018)

Requires government data assets to be published as machine-readable data in open formats
Requires Chief Data Officers (CDOs) to be appointed at federal agencies
Requires CDOs to develop and maintain comprehensive data inventories
Has led to a proliferation of data science roles in the federal government

Open Source Intelligence

More than 90% of the analysis in the intelligence community is based on open source information
Government agencies use a lot of the same datasets that we will be using in this class
Yet the OSINT community has only begun to scratch the surface of what is possible with data science

Monitoring, Evaluation and Learning

Another important use of data in international affairs is monitoring, evaluation and learning (MEL)
MEL is a process that helps organizations track and assess the performance of their programs
MEL is a key component of the evaluation strategy of the World Bank and other agencies
A major component of MEL is the use of randomized control trials (RCTs) and other designs, which you will learn about in this class

Skills/Knowledge You Will Gain

R coding skills (and RStudio), with focus on “tidy” approach and reproducible research
Quarto (html documents, PDFs, presentations, websites, books, blogs, …)
How to access and “clean” data so that you can analyze it
When you hear terms like “machine learning”, you’ll have some sense of what people are talking about

Structure of the Course

Data Visualization
- Summarizing and communicating effectively with data
Statistical Inference
- Making rigorous conclusions from data
Modeling
- For prediction and forecasting
- For drawing causal conclusions

How do I get an “A”? (requirements)

Labs (20 percent)
3 Data Analysis Assignments (45 percent; 15 percent each)
Final Project (20 percent)

Course Website

https://quant4ia.rocks
Let’s take a quick tour!

Install R and RStudio

If you haven’t already…
Go to the RStudio download page
Download R and then RStudio

Set up RStudio

Go to Tools>Global Options
Under Code, enable native pipe operator (|>)
Under Appearance, choose a theme
Configure panes
- Go to Pane Layout
- Move Source, Console, etc. to preferred positions

Illustration

Install key packages

Install the Tidyverse group of packages from the console
- install.packages("tidyverse")
Install devtools
- install.packages("devtools"))
Install tinytex (for PDF rendering)
- Go to your terminal and type quarto install tinytex

Illustration

Let’s get going . . .

Your first data visualizations…

(and making sure we have R and RStudio installed and ready to roll)

Example: Make a map!

Example: Plotting Democracy Over Time

Example: UN Voting Trends

Your Task

Make sure R and RStudio installed (we can help if needed)
Create a folder for this class somewhere on your machine
- Create a sub-folder called “classwork”
- Download and save week1-classwork.qmd in that folder
Open the week1-classwork.qmd file in RStudio, which has code for 3 data viz activities
- Map making
- Democracy Over Time
- UN Voting patterns
Follow the instructions to update the code
Click the little green arrow to run the code chunk
Click Render to update your HTML output
Complete as much as you can (no problem if you do not finish)