Peter J Wilcoxen > PAI 789 Advanced Policy Analysis

Poster Session Schedule for Spring 2020

There will be four 15-minute rounds during the poster session. During each round, there will be four or five people ready to talk about their projects in separate breakout rooms. The rounds are shown below and the number by each person's name indicates the breakout room they will be in during that round. Also, each person's name links to the GitHub repository for their project.

Round 1

  1. Laud Boateng
  2. On March 11 2020, the World Health Organization declared Covid-19 a pandemic. My project 1.analysis flu trends in Ghana for the year 2020, 2.construct a disease risk index for Ghana and 3. Provides insights on Ghana's Flu season for 2020 (May to July).The data is sourced from the DHIMS-2 Health information database of the Ghana Health Service. The Ghana Covid Risk Index project will provide summary statistics and use data visualization tools describe the disease and risk burden in Ghana.
  3. Phoebe O'Connor
  4. The share of coal-powered electricity generation has dropped by 54% in the past 19 years in the US. This project examines whether or not this decline has occurred evenly across US states.
  5. Linh Nguyen
  6. Greenhouse Emission Patterns in EU Member States
  7. Jen Raichel
  8. Using this data to understand reports of Coronavirus and related deaths affecting people of color, specifically African Americans, at higher rates than it does white people.
  9. Lauryn Quick
  10. This project provides a basic exploratory analysis of poverty and inequality statistics in the United States. Using Census 5-year data for 2018 and 2012, this analysis compares top-level county poverty estimates and Gini coefficients and identifies U.S. counties with the highest poverty rates and those with the largest percentage-point rate increases and decreases over time. Finally, the project aspires to create a script template that can be applied to explore census tract level demographic characteristics in the counties identified as high poverty.

Round 2

  1. Nicholas Ramos
  2. A classic topic for data analysis, generating exploratory data for crime in Chicago, Illinois is a project that offers a variety of opportunities to identify relationships and trends with data. However, this ultimately depends on the data each burgeoning data analyst decides to integrate-for this project, I will use updated data files (2001-2020) to engage in exploratory analysis with regards to crime, unemployment and weather variables. Also, while not a deliverable, a series of basic bar and pie graphs provided me with an initial excursion in generating visual representations of data with matplotlib and and plotly.
  3. Cole Ware
  4. This analysis aims to determine whether the VA clinics in Northeast Ohio are equally accessible to veterans across age cohorts.
  5. Kaitlyn Simmons
  6. The scripts set up a heat map of unemployment in Georgia from 2005-2015. GIS is used to create images for the heat maps. Another script creates a gif of the heat map and a final script analyzes the carbon dioxide emission rates in Georgia by year to compare any differences.
  7. Mahin Tariq
  8. TBA
  9. Phoebe Aguiar
  10. Independent project analyzing the relationship between the prevalence of high risk population and Corona Virus cases in California.

Round 3

  1. Jack Baldwin
  2. This process uses spatial joins, field calculators, and seaborn visualizations to better understand per capita wildfire burdens utilizing geographical hierarchies as scoping levels. NASA MODIS satellite data was used as fire observation inputs and catalogued according to US Census shapefiles.
  3. Cameron Keys
  4. DoD R&D FY21 spending geographic distribution projection
  5. Yu En Hsu
  6. Python script for scraping electricity scooter subsidy data from Taiwan government websites, cleaning collected data, and analysis.
  7. Katie Medina
  8. Analysis of Potential Bus Rapid Transit Locations in Boston, MA

Round 4

  1. Fama Ndiaye
  2. Analyzing the price of commodities used by the World Food Program.
  3. Peiting Chen
  4. This presentation focuses on how much 2 candidates of 2016 election get from individual contributions, Hillary and Trump, and how the condition change from primary election to general election.
  5. Katie Smith
  6. An analysis of various factors that could impact the infant mortality rate in South America in 2016 reveals that although GDP per capita, percent of deaths caused by communicable diseases, and adolescent fertility rate are correlated, only GDP per capita is significantly associated with infant mortality rates.
  7. Jiyoung Park
  8. Exploring factors that can explain the state of the spread of COVID-19.
  9. Sparsh Kansal
  10. Back in January 2010, the NYC District Attorney's office implemented a program designed to reduce the felony re-arrest rates city wide. The individuals arrested after the implementation of the program in certain precincts were provided with on-spot intervention by New York Policy Department. The DA's office hopes providing interventions will reduce the probability of arrested individuals committing a felony crime in the next one year. This repository evaluates the impact of the program developed by NYC District Attorney's office and recommends continuing the program after evaluating its impact on the felony re-arrest rate employing the probit regression model on the provided data.

People Not Presenting

Ali Ehsan
This project provides an analysis and evaluation of the impact of extreme weather on the time to complete a 'Sewer Back up' problem in the City of Syracuse, New York.
Roberto Quijano
From 2008 to 2018, nearly 40,000 disappearances were recorded in all 32 Mexican states. As a response, the federal government set up the National Registry of Information of Missing and Disappeared Persons. States that have higher presence of organized crime are those that have the most disappearances. Particularly, northern states present the highest numbers of disappearances even when adjusting to a rate per 100,000.
Haley Smith
The purpose of this script is to compare the date at which states implemented stay at home orders and the predicted deaths per state as well as the predicted length of social distancing measures.
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Peter J Wilcoxen, The Maxwell School, Syracuse University
Revised 03/08/2021