By Tyler Hanson and Andrew Harnish
Introduction
This project analyzes the effect of locations, like police stations, parks, and technological resources on factors of education. We use the Haversine formula to calculate the distance between two points of longitude and latitude, counting the total number of sites within a given radius of any given school. We then average together these counts to create meaningful statistics and measures to quantify location’s impact on education within Chicago.
Data Sources
Chicago School Data from 2011-2012
Contains information about various school statistics, like student wellness factors, academic progress statistics, and school locations. The set includes high schools middle schools, and elementary schools.
School Data
Chicago Park Data from 2016 and earlier
Contains information and locations of all parks in Chicago. (Data is deprecated, but it contains the same years as our school data set does).
Park Data
Chicago Police Data
Contains information and locations of all police stations in Chicago.
Police Data
Chicago Public Technology Resources Data
Contains information and locations of libraries, community technology centers, and youth centers.
Technology Data
Chicago Crime Data from 2011-2012
Contains information and locations of all crimes recorded in Chicago from 2001 to the present. For our purposes, we only analyzed data from 2011 and 2012.
Crime Data
Terminology
Safety Score - Score from one to ninety nine based on student perception of safety. Results are gathered from surveys given to the school.
iSAT - comprehensive tests given to both students and teachers multiple times throughout the school year to track progress and learning.
ZIP Code and College Enrollment
This bar graph displays the average number of students enrolled in college from schools in each zip code. Some zip codes have significantly higher averages than others, meaning there is a correlation between a school’s location and how many students who attend college.
Rate of Misconducts Over Chicago
Every circle on this map represents a school in our data set. The larger the circle, the higher the rate of misconducts. Some areas on the map have much higher concentrations due to the higher density and increased size of circles. In these areas misconducts occur regularly. In contrast, areas with a high density of small circles, have little to no misconducts per year. Areas to note from this graph are the high levels of misconduct in North West Chicago and South Chicago, and the low levels of misconduct in North Chicago and Downtown Chicago.
Safety Score and Parks
On the y-axis, the average safety score for each group of schools with the same number of parks in a specific radius. On the x-axis, the amount of parks within a specific radius is labeled. The size of each point is the count of schools being averaged, displaying magnitude. Overall, this graph displays a split distribution, when at 16 parks within a 1.1 mile radius students start to feel significantly safer in their school environment.
Safety Score and Police Stations
On the y-axis, the average safety score for each group of schools with the same number of police stations in a specific radius. On the x-axis, the amount of police stations within a specific radius is labeled. The size of each point is the count of schools being averaged, displaying magnitude. Over all the categories in our data set, none seemed to correlate with a school's distance away from a police station. This is most likely because the number of police stations is drastically lower than that of parks and crimes in chicago. This means that minor outliers within our dataset are able to hide correlations.
Technological Resources and ISAT Exceeding Math %
On the y-axis, the average iSAT math score per school is listed for each group of schools with the same number of technology resources within a specific radius. On the x-axis, the amount of technology resources within a specific radius. The size of each point is the count of schools being averaged, displaying magnitude. As the amount of technology resources increases beyond 30, we start to see a noticeable increase in average iSAT math scores. Although the magnitude of these points is very small in comparison to the rest of the graph, we can extrapolate that if more data was present, we would be able to see a stronger trend.