For many years now, data has been placed into simplistic visualizations for its readers to view. The problem with this: the word simplistic. Although it is useful for readers and viewers to be able to see a statistical data set in just a chart, it leaves a lot of things out. There is no way that a massive, complex research project can be boiled down into just a few charts or pie graphs. And here lies the problem with visualized data – it’s misleading.
Even if it doesn’t have to do with research or complexity, graphs are also often misleading in terms of public opinion or statistics regarding our country. For example, this graph displaying how many Republicans, Democrats and Independents agreed with a court ruling. In the graph, the bar for the Democrats appears to be about three times larger than the bar for the Republicans and the Democrats. This makes it seem that three times more Democrats supported the decision than either the Republicans or Democrats. However, this is not the case at all because the left axis doesn’t start at zero. Instead, it only goes from 50 to 64 percent, therefore making any deviation seem much larger. Had the graph’s axis begun at zero, the difference in support would appear to be much smaller. This is what I mean by data misrepresentation – people who make the graphs can alter them to have them display very different meanings that the actual data represents.
While this may not seem like a large problem in society, in can turn out to be. When reliable news stations release media, people just take them without questioning it when it may be completely misrepresented. However, most people in this day and age don’t question what they are being told – they just accept it. Especially if it comes from the government or a source that they have relied on and trusted for a very long time. With new technology it is important that people actually pay attention to what they are looking at.
“Misleading Graphs: Real Life Examples.” Statistics How To. N.p., n.d. Web. 02 Nov. 2014.
Drucker, Johanna. “Humanities Approaches to Graphical Display.” DHQ: Digital Humanities Quarterly:. Digital Humanities Quarterly, n.d. Web. 03 Nov. 2014.