Regina it is nice the way you explained how statitics can be used to misrepresent data in advertising but also i can add thatgraphs that are ambiguous or cluttered do not allow clear interpretation of results whichincrease chances of misrepresentation. Absence of labels scales and data elements also increaseerrors in data representation and mislead the reader (Brotton et al. 2010). A typical example ofdata misrepresentation is the one commonly observed during promotional activities of a newdrug into the market. Often it could be observed that the clinical trials performed and resultsobtained on the use/significance of the medicine are unnecessarily augmented to highlight
quality or effectiveness of the medicine. However the medicine may be less effective or mightcontain adverse side effects that the researchers or company are aware which is never mentionedin reality. In some situations pie charts the most easily understandable graphics are used torepresent results in studies conducted with incomplete data or missing variables (Pavlovich-Danis 2012).
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