Please Respond to the following post with a paragraph, add citations and references.

Graphics and statistics can be used to misrepresent data ALL THE TIME. Using certain biases and presenting certain information in a way can lead a reader in a certain direction, misrepresenting a mathematical, objective number. It is important to know where information is coming from and how it is achieved since objective numbers may not be objective at all.

In statistics, a sample— that is, a small subset of a larger set of data — to draw inferencesabout the larger set. The larger set is known as the population from which the sample is drawn. A misrepresentation of the sample group can come from handpicking this sample group to one’s he time in wanted outcome. This can be considered a bias sample.

Also, the misrepresentation of data on graphs can largely influence someone reading the graph if one doesn’t look closely at the numbers set forth. For example, as Project Leader David M. Lane writes about in his introduction from Online Statistics Education, the use of pictures and “fanciness” as he puts it instead of plain bars on a graph can distort or exaggerate differences in key data. He talks about using different-sized pictures of computers on a chart rather than simple bars. There is a humungous looking computer next too very small computer to show a large difference in how many people buy Macs instead of PCs. The distortion ratio in the pictures is 35:1 rather than the actual ratio of data being 6:1. Another example he writes about is the use of the Y-axis on a chart. Instead of setting the baseline of zero as it should be, one can set the “zero” mark to be 50 focusing or zooming in on the bar graph to the differences, rather than the whole picture.

We see these misrepresentations all the time in advertisements so products can be sold to customers. One particular advertisement genre that gets me every time are political ads. Never mind the “negative” campaigning to slam another opponent, but when they represent data, it is a complete bias representation. One only hopes people see right through these ads but most of us do not. DO your due diligence in researching your facts. We are our own fact-checkers!

“Introduction,” by Project Leader: David M. Lane, from Online Statistics Education: An Interactive Multimedia Course of Study

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