How to Lie with Statistics

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To create the following two graphs, I first extracted data from the “Actual and Legal Progress toward Sheff I Goal, 2003-2007″ chart featured as Figure 5.1 in Dougherty’s Sheff v. O’Neill: Weak Desegration Remedies and Strong Disincentives in Connecticut, 1996-2008. In an excel spreadsheet, I entered years into Row A and the corresponding progress percentages into Row B. I then highlighted the data, accessed sub menus at the top of the excel menu bar, and selected a line graph. To skew perspectives of progression, I altered the scale of each graph by adjusting the axis limits to portray extremes.

The first graph, pictured to the right, denotes a drastic positive change in over just a few short years. To achieve this look I set the axis limit to 0.32, just under the 0.35 percent mark, to represent a skewed data plot illustrating sweeping positive progression.
In the second graph, I strategically selected axis information that would cause the reader to speculate a less dramatic change occurred over the same short time period. To produce this graph, I increased the range of the axis significantly and even put the range into negative figures causing the reader to infer that growth was steady but slow.
These two different depictions of data represent the same information in the same format with the goal of eliciting a certain response from its audience. Altering just a few seemingly insignificant settings yields significantly different outcomes. The power of this post is revealed in the simple truth that anyone, anywhere can alter any set of data to support virtually any argument by portraying a certain set of facts (that unfortunately an overwhelming majority of readers assume to be concrete, fixed, and true) in a mischievous light. Ultimately, it is important to recognize that statistics don’t always tell a true story.