A portfolio of projects I created to grow my coding skills in R, Python, ArcMap and Powerpoint. While I address several different topics, my projects cluster around focuses on international development and humanitarian data and the politics of fragile states.
I hope you enjoy exploring the data alongside me.
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R
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How Fast is COVID 19 growing in the US? The other day my mom asked me "Tim, how quickly is covid actually spreading", and I realized this is actually a difficult question to answer. People are used to thinking about geometric growth, the staight lines of
$y = mx + b$ . But the behavior of a virus in the early stage of an epidemic is close to exponential growth,$y = e^{ax}$ . This demonstration uses some simple graphing and fitting to teach readers about the growth of COVID-19 in the US over the past two months. -
Inferential Statistics: Does a dietary supplement make people smarter?: A dietary supplement marketer has organized a study to investigate the effects of their product. They had randomly assigned students take different supplements or none, then complete mental math problems as fast as they good. But did the supplements really make people smarter?
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Visualizing Survey Data and Linear Regression - Attitudes toward Syrian refugees among rural Jordanians: Uses survey data from humanitarians to vizualize correlations between demographic characteristics and attitudes toward refugees. What subsets of Jordanians have particularly trusting attitudes toward Jordanians?
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Data Visualization: The Natural Resource Curse: In this demo, I will make an economist style plot from a multiple country linear regression. For my data I will use country level data from the seminal paper "Natural Resource Abundance and Economic Growth" by Sachs and Warner, which argued that the presence of natural resources in a country caused lower growth.
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Python
- Supervised Learning Project: Predicting Political Attitudes with Developing Country Government Data: This code attempts to create a model which uses administrative data available to authoritarian developing states to predict attitudes toward the authoritarian regime, with supervised learning. The data used comes from a social cohesion survey conducted in Armenia in 2011. Results are inconclusive, and are meant purely as a demonstration of grasp of machine learning concepts.
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ArcMap
- Refugee Assistance Programming in Northern Jordan: This thematic map was produced for Agency France for Technical Assistance (ACTED) to advertsie the breadth of their programming to prospective funders. They also mounted it on the walls in their field offices, which I was flattered by.
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Powerpoints
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Parents First Advising Sample: This is a powerpoint presentation written for a fictional charity in Cote D'Ivoire that wants to improve their impact on early childhood development. It describes some of the current issues in their monitoring program and advises on practical next steps in targeting data and impact evaluation. It was written as a timed skills-test for Innovations for Poverty Action, so it was completed in just two hours.
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Dams of Jordan Social Cohesion and Area Mapping Report : This powerpoint presentation describes surveys for location targeting in rural Jordan. The survey was commissioned after violence between community members and refugee cash for workers threatened the viability of GIZ's programming. It was given to GIZ and Jordanian Ministry of Water Staff.
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