Use of Graphics and Statistics to Distort Data

Use of Graphics and Statistics to Distort Data

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January 16, 2018

Graphics and statistics can be used to misrepresent data

There are different ways in which a person can manipulate and distort data by taking advantage of statistical and graphical contents. A classic example is the consumption rate in the United States which is a result of graphically inducing yet misleading advertisement. The public can believe anything if persuaded by concocted numbers. People tend to blindly assume that the figures represented in ads are sound and scientifically proven facts. For example, Dettol soap advertisement that alludes that it has 99.9% effectiveness in germs destruction. However, there is a possibility of data being misrepresented through errors arising from samples or mistakes made by people conducting surveys or research (Groves, 2004).

A difference in the population and the chosen sample can mislead findings of a survey. Furthermore, samples cannot always represent the actual characteristic of a population. This is witnessed in differing opinion polls as a result of the different choice of samples though not too large extent. Another example is the 1936 election case. The literary digest had surveyed who will clinch the presidency. The company had forwarded mock ballot papers to random names which they acquired from directories and subscriptions by members. Only two million, four hundred thousand responses were received out of the ten million papers sent through the post (Qualtrix, 2010). This created a sampling bias, and it was inconclusive to decide that London would tramp Roosevelt based on that sample.


Groves, R. M. (2004). Survey errors and survey costs (Vol. 536). John Wiley & Sons.

Qualtrix (2010). The 1936 Election – A Polling Catastrophe | Qualtrics. [online] Qualtrics. Available at: [Accessed 16 Jan. 2018].