Fall Data Challenge: Resources Roundup, Stats to Fight Homelessness

This year’s Fall Data Challenge theme is “Help Solve Homelessness,” so now it’s time to dig into the details of this important and complicated issue.

On an average night in 2018, 553,000 people in the US experienced homelessness—an increase over 2017. Great minds all over the country are dedicating their work to help those experiencing homelessness and find creative solutions to address the issue at large. Statisticians are a crucial part of how we’re gaining a deeper understanding of the homelessness crisis and contributing to the effort to mitigate this crisis.

This resource roundup offers some recent examples to get you inspired and excited to get to work on your team’s submission.

LA Times: Statistical error inflated last year’s homeless count by more than 2,700

Here’s an important example of what happens when statisticians get their predictions wrong, but also why statisticians are essential to finding potential solutions for the homelessness crisis. In 2017, statisticians noticed an error that inflated the number of people experiencing homelessness in Los Angeles.

Pacific Standard: Why Can’t We Get An Accurate Count of the Homeless Population?

The homelessness crisis is a complicated and nuanced issue, in part because it’s difficult to count the number of individuals experiencing homelessness. Counts are conducted by volunteers on one specific night in order to get a general estimate of the population, which in turn impacts funding to programs that help those experiencing homelessness.

End Homelessness: State of Homelessness Report

These interactive graphics will help you get a better sense of the raw data included in this year’s dataset. See data on specific geographic regions, information on race and ethnicity, and breakdowns of people experiencing homelessness by category, like veterans, families, youth, individuals and those who are chronically homeless. With the amount of data available, it’s important to look at the data from many different lenses.

Data Cookbook

This year’s dataset from the Department of Housing and Urban Development is very robust, so we’ve taken a few common terms and defined them in order to give you a head start in analyzing the data. Be sure to put this handy reference to work as you and your team explore the dataset!

City-Specific Resources

For this year’s challenge, teams must choose to focus on one of the three cities listed below. Every city is different, and understanding the local homelessness crisis will give you additional perspective into the data.

New York City

New York Times: New York’s Toughest Homeless Problem

This New York Times article will give you perspective into the complicated situation around homelessness in New York City, which has the largest population of people experiencing homelessness in the US.

Los Angeles

CNN: He was a Yale graduate, Wall Street banker and entrepreneur. Today he’s homeless in Los Angeles

When looking at a topic as complicated and people focused as homelessness, don’t overlook the unique stories of the individuals currently experiencing homelessness. Shawn Peasants, who is featured in this CNN piece, said “”It means it can happen to anybody. It’s a problem we all could face.


KOMO News: Growing numbers of Seattle’s homeless found housing this year, city reports

As the number of people experiencing homelessness in Seattle grows, the city is working on a plan to both prevent individuals from becoming homeless and helping those who do not currently have a permanent residence.

Learn more about the Fall Data Challenge and how to submit your entry here.



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