How to Lie with Maps

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Widespread Racial Diversity

Sharp Racial Differences

These two maps display the same data from the racial composition of students in the Hartford area for the 2009-2010 academic year. Both of the data visualizations are mathematically correct, in that they both represent the accurate data, but the two maps are designed differently which can lead viewers to have inaccurate perceptions of the data. The first map shows Hartford and its surrounding neighborhoods as racially diverse by displaying a large number of buckets that divide the data and by using a good range of colors to represent a wide variety of racial compositions. The second map is only divided into three ranges: 0.0-0.25, 0.25-0.75, and 0.75-1.0 and visually it looks like there are sharp racial differences. The color choice goes from the lightest color representing the range with the smallest percentage of minorities to the darkest color representing the range with the largest percentage of racial minorities which causes the viewer to immediately recognize the sharp racial differences by town.

Excercise 7: How To Lie With Maps

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Racial Diversity in Hartford Area Schools: 2009-10

Racial Diversity in Hartford Area Schools: 2009-10

The two maps above display the same information. Interestingly enough, I was able to use the same data and display two completely different interpretations of that data using Google Fusion Tables. Although both maps represent the same numerical data, the geographical representations may look entirely different because of the ability to switch the way each county is set up and the number of “buckets” (data sets) I wish to be shown on the map. The first visual map depicts a very diverse Hartford area, each bucket representing different percentages of minority students enrolled in schools. Because there are a total of six buckets represented in the first map, one can tell that the area being observed is diverse- one can see the different amounts of percentages in each area within the map that represent the differing town statistics. On the other hand, the second map shows very little diversity in the Hartford area. The data interpreted in the second map is exactly the same to the first, but the legend shows that in the second map there are only a few “buckets” of numerical data to be represented on the map. As one can see, the map then shows large amounts of shaded regions in one area of the map, whereas it looks less concentrated in the middle of the map. The simple alterations of the number of buckets being represented in both maps allows for the maps to depict same data in differing views-one showing more diversity (different shaded regions), and another one showing less diversity (large amounts of one color overbearing the entire map.

Lying with Maps

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How to Lie with Maps:

Map Depicting Much Racial Diversity in Hartford School Districts, 09-10

Map Depicting Little Racial Diversity in Hartford School Districts, 09-10

Both of these maps display the same data; however, each graph tells an entirely different story. The first graph depicts a racially diverse neighborhood. In contrast, the second graph shows a huge disparity between segregated schools and non segregated areas. The way in which I was able to portray such a disparity, was by selecting different margins for the data. For example, the first graph utilizes over five different “buckets” as denoted on Google Fusion Tables. These “buckets” represent categories of change in terms of percentages. In the second graph, however, I only used two “buckets.” Therefore though the data is the same, the numbers are presented quite differently, giving what appears to be different results.

Exercise 7: How To Lie With Maps

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Sharp Racial Divisions

Widespread Racial Diversity

The two maps above both depict the same data for the percent of minority students in Hartford-area school districts for the 2009-2010 school year. However, the first map shows sharp racial divisions in the Hartford area, while the second map portrays widespread racial diversity. By editing certain aspects of the map, the data can reveal drastically different interpretations of the racial composition of Hartford-area schools. For example, in the first map, I decreased the range of the data and the amount of gradients to only two so that the map would portray major differences between the districts. I also chose to use contrasting colors, one very light and the other very dark, to portray major disparity between the regions. In the second map, I increased the range and the amount of gradients to make the Hartford area appear very diverse. I also chose to use different shades of purple for the gradient, because this makes the map appear to have little contrast between regions.

Exercise 7: How To Lie With Maps

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Hartford Area School Racial Diversity (2009-2010 Academic School Year)

Hartford Area School Racial Division (2009-2010 Academic School Year)

Using the data from the racial composition of students in the Hartford area, both of the data visualizations are mathematically accurate towards representing the racial composition of Hartford area schools during the 2009-2010 academic school year. However, each visualization depicts a different story because of the different ways the maps are designed. In the first data visualization, the visualization demonstrates a seemingly racially diverse Hartford area. In order to demonstrate a racially diverse Hartford area, the legend is divided into many different shadings, each demonstrating a different percentage of minorities present in each area. The process of increasing the amount of buckets used in the visualization can allow for more shadings to be represented in the graph. The more shadings that are represented, the more racially diverse the area seems. In the second visualization, however, there is a different picture painted with the same data. Since the second visualization only has three buckets incorporated, the map then limits more data to be shown. Thus, using larger gaps in the legend would produce sharper racial divisions among districts.