Data Misrepresentation Using Statistics and Graphics

Data Misrepresentation Using Statistics and Graphics

Statistics and graphics are influential platforms used to giving ideas based on historical trends of data, as well as, other factors. In most cases, they provide viewers and users with a measure of likelihood of viewing a particular outcome. However, both of them can be used to misinterpret data either intentionally or accidentally depending with the motive or interests of the presenter. Working with data is restrained by the availability of variables or data when making analysis or making assumptions to achieve a desirable outcome – and this may be true or false. Assumptions do not provide a clear picture of what is being represented – and without any concrete theoretical and evidence grounds, the person analyzing the data would automatically make falsified recommendations or suggestions. Such an aspect tells that a non-factual data source probably leads to misleading statistical information which gives a false publication for the public to consume. 

Considering the American society, the people are heavy consumers of advertisements and polls used in politically-oriented surveys and marketing activities such as consumption of particular goods. Actually, the public tends to believe in persuasive numerical facts, however, the fact that many statistic-based researches is based on sampling procedures, human and sampling errors are two limitations that would lead to data misrepresentation or bias. There are several examples which can be picked randomly to prove how data presenters can misrepresent data and graphics to communicate a certain phenomenon. A good example of misleading graphs was seen with a post in the Weekly Standard by Daniel Halper dated August 8, 2012 which reported the number of people receiving federal welfare. 

Graph 1: Federal Welfare Report, the Weekly Standard

Based on the above graph, it looks like the US welfare problem looks more spiraling and out of control from the general view. However, looking at the Y-axis of the graph, it starts at 94 million. Another example was seen in the Fox News report of 2012 GOP preference poll which used an abnormal pie chart to represent its data to the public. Considering its pie chart below, the percentages do not add to 100% assuming the rules of a pie chart (Hickey, 2012). 

Graph 2: Fox News 2012 Presidential Run

References

Halper, D. (2012). Over 100 million People Now Receiving Federal Welfare. The Weekly Standard August 08, 2012. Accessed from http://www.weeklystandard.com/over-100- million-now-receiving-federal-welfare/article/649589 Hickey, W. (2012). Exposed: Here are the Tricks that Fox News Uses to Manipulate Statistics on it Graphics. Business Insider. Accessed from http://www.businessinsider.com/fox-news- charts-tricks-data-2012-11