When presenting data and trying to put research into a
picture people can understand, scientists use a wide variety of graphs and
charts. This is all for the sake of interpreting their data… usually. There are
those few times where one finds that graph that seems a little, well, off or even biased.
This bad data can skew the perceptions of the people
who read it about the subject or issue in question simply because those who
made the graph desired a certain effect from it. People can read about things
all they want, but graphs and numbers can really put things into perspective. This
makes it all the easier to manipulate data the slightest bit with a bad or biased
presentation.
See the graph below:
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| Description: This graph shown on Fox News about six years ago was supposed to be a representation of the 2012 Republican presidential nomination. More specifically, it aimed to show, in percentages, how much chance each candidate had of being nominated. The candidates were Mike Huckabee, Mitt Romney, and Sarah Palin. The graph showed that Huckabee had a 63% chance, Romney a 60% chance, and Palin a 70% chance. Source: https://www.nbcchicago.com/news/local/FOX-News-Chart-Fails-Math-73711092.html |
Now, I am sure that viewers noticed something right
off the bat. The chart has a glaringly obvious issue. The fact that it is a pie
chart means the percentages must add up to 100%. However, these three add up to
193%. This is the main problem that really caught my eye. How these numbers ended
up being represented this way is beyond me, but something definitely went wrong
in the math. Another thing: even just two of them added up together already
breaches 100%. Why are they all so high? This makes it seem like all the Republican
candidates have a high chance of being nominated and that they are almost
equally popular, though the viewers of the graph would still get the impression
that Palin was still most likely to win.
What is even more baffling is that this fairly inaccurate
chart was shown on a well-known news channel for all to see. This certainly
must have discredited their information and sources somewhat. The creators of
the graph should perhaps see about checking their math next time. Whether these percentages were expressed this way purposefully or accidentally, always remember: don't be fooled by bad data.
