Graphs are often used to deliver a visual and compelling case in many applications and businesses. Graphs are the information delivery vehicle of choice for many numerical data applications. With graphs a lot of information can be condensed into a visually descriptive object. They reduce the amount of time that would have been expended in reading or parsing through a lot of information.
On the other hand, they can also be easily used to misrepresent or skew interpretation towards a favorable outcome. With modern tools like Microsoft Excel, graphs can be made to look more visually appealing and creative. Such appeal could often be used to mask incorrect or misleading information. Robyn Raschke and Paul John Steinbart argued that training users on graph design and making them aware of proper design would often reduce the problem of poor or bad graphs but would not eliminate it altogether (Robyn Raschke & Paul John Steinbart, 23).
There are far too many examples of poor graph in use in the media and other less formal online sources as well. The prevalence of advanced graphing capabilities like those found in Microsoft Excel can lead poorly trained people into creating these graphs (Levine et al. 57). The availability of these advanced graphing tools make it a lot easier to produce bad graphs with a visual appeal. People may be less inclined to over emphasize the visual appeal of graphs if they understand that it is more important to be informative than persuasive (Booher Dianna). A striking graph design can improve the clarity of the information delivered hence this tendency can be easily understood. The effectiveness of such visually appealing graphs could lead to people repeating these mistakes because they assume it must be the correct way to present information.
The study by Robyn Raschke & Paul John Steinbart emphasized two methods of intervention that could improve graph designers. In the first case they sought to have them justify their...
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