FINAL: USA Mean Composite SAT 2014 Scores with Percent Participation by State

The purpose of this project is to geographically represent the mean composite SAT scores and participation rates by state for the entire United States of America (USA) as if prepared by the National Center for Education Statistics of the U.S. Department of Education for an article on high school seniors and college entrance scores by the Washington Post. The project uses the college entrance exam scores (SAT scores) for 2014 high school students and test participation rates for 2014 college bound seniors from the College Board and 2017 U.S.A. boundaries from the U.S. Census Bureau. The SAT scores are a mean composite score of all 3 test scores sections, averaged together by state. The final bivariate map employes Gestalt's principles of visual hierarchy, contrast and figure-ground to show mean composite SAT scores as proportional symbols on an underlying choropleth map with percent participation by state. Both datasets were incorporated on one map utilizing ArcGIS Pro software. Datasets were tabulated in Excel, imported into ArcGIS Pro and combined using the Add Join tool.
By creating a bivariate map that cartographically represents both the percent student participation rate and the mean composite SAT score per state, the final product of this project effectively communicates the relationship between participation rate and mean SAT score. By using a sequential color scheme, the audience can easily determine which states have low and high participation rates. Additionally, by representing mean composite SAT score with proportional symbols, the audience can easily determine the states with low and high scores.
From the data on the map, the relationship between participation rate and mean composite SAT score can easily be determined. The relationship is an inverse one where the highest participation rates have the lowest scores, while the states with the lowest participation rates have the highest scores. It is evident that participation rate has a large impact on state mean composite SAT scores. While this seems counter intuitive, many factors contribute to SAT participation rates. Typically the top scoring students are the ones who elect to take the exam, so states with low participation rates mostly include those students who will do well which results in artificially higher SAT scores. Whereas, in states like DC, all students are required to take the SAT, which includes those students who many not do well or are not intending to attend and prepare for college, resulting in a naturally lower mean SAT score. These results demonstrate why mean composite scores should not be the only measurement used to rank or evaluate a state's educational system. 

Comments

Post a Comment

Popular posts from this blog

Module 6: Proportional Symbol and Bivariate Choropleth Mapping

Image
The objectives of this week's lab was to explore proportional symbol and bivariate choropleth mapping techniques, as well as customizing legends for each technique. One of the data sets for this lab included positive and negative values. The final map utilizes proportional symbols to show both positive and negative values. This map is essentially two proportional symbol maps overlaid on each other, one for positive job growth and another for negative job growth, with the symbols for both variables sized the same. Utilizing proportional symbols to show both positive and negative values is an effective way to visualize areas that show the greatest and lowest values. These areas are easy to see quickly on the map and give the map reader a simple way to visualize the variable being mapped. Fig 1. Proportional symbol map using positive and negative values.  Another data set for this lab examined contained two data variables: percent of the US population in each state that is obe
Read more

Module 2: Coordinate Systems

Image
In this week's lab I explore different coordinate systems and projections in order to better understand the nature of distortions introduced by the systems. For the last part of the lab, I was tasked with selecting a state in the contiguous US and selecting an appropriate projection for the area. I selected the state of Wyoming as my area of interest. Wyoming has 4 State Plane zones and two UTM zones, so neither a single State Plane nor UTM system would work for this area without distorting the size or shape of the state. Therefore, the best coordinate system for this area is Custom Coordinate system. I chose NAD 1983 WyLam (Meters), a custom system specifically for the state of Wyoming, as the projected coordinate system. This coordinate system is a Lambert secant-case normal-aspect conic type projection which preserves shape and is appropriate for a general reference map. The standard parallels are placed at 41N and 45N, the boundaries of the state of Wyoming, which minimizes
Read more

Module 4: Color Concepts & Choropleth Mapping

Image
In this week's lab, I explored using color and selecting color ramps in ColorBrewer, as well as applying these concepts to create meaningful choropleth maps. I created a map of population change from 2010 to 2014 in Georgia counties. I normalized the data and produced a choropleth map of population change using a diverging color scheme with 6 classes divided around a midpoint of 0. Fig 1. Choropleth map of population change in Georgia counties using a diverging color scheme. For the Georgia population data set, I chose to divide the data set into 6 classes around a midpoint of 0: 3 showing a decrease in population and 3 showing an increase in the population. The classes were grouped based on a manual classification closely based on the Natural Break classification, where the midpoint was adjusted to 0 with the other groups unchanged. Natural Breaks classification creates classes based on similarities in values in the data, thereby revealing patterns in the data. By adjust
Read more