How to Avoid Misleading and Exaggerated Graphs Guidelines

Misleading and Exaggerated Graphs
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Misleading and Exaggerated Graphs
The manipulated data that caught my attention depicting misleading and exaggerated graphs is the data news from Washington Examiner. The data was presented by the U.S. Census's Survey of Income and Program Participation showing over one hundred million United States citizens receiving federal welfare. The data showed that close to 110 million people were receiving welfare benefits (Halper, 2012). However, the presented figures were exaggerated and unrealistic because different variables were not factored into the data, such as health insurance premium subsidies or Earned Income Tax Credit. Looking at the graphical presentation of the data for the first time, it is notable that several evidences are misleading guidelines based on the figures presented.
The graph's Y-axis is manipulated, and this is one of the common misleading graphs' guidelines. The data in the graph involves large numbers, and closer scrutiny shows the graph has excluded the zero from its Y-axis. Most analysts remove the zero from the Y-axis to present instances' disparity in a comprehensive way. However, the graph lacking a zero in its Y-axis may show biased information. The action is misleading by seemingly blowing up the disparities between the variable. The graph presented by the U.S. Census's Survey of Income and Program Participation shows a doubled number of American citizens getting welfare benefits (Halper, 2012). Also, more graphical exaggeration is seen where the graph starts from ninety-four million; the differences between the variable are extremely biased and exaggerated.
If I were the analyst, I would present the graph differently by following the following guidelines. First, I would include the value in the visual presentation. Having the zero value in the Y-axis will make it easy to read and interpret the data (Noutahi et al., 2019). I would also use scale intervals that are realistic, uniform, and easy to interpret based on the variable presented. Since the data involves government expenditures, it is essential to make it reliable, concise, and easy for citizens to interpret. Secondly, if the data does not allow the inclusion of the zero value, I would use a zero break to indicate the zero valu...