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Spotting Visualisation Lies

You’re all familiar with idea of a political spin doctors manipulating information to suit a particular means. However, in the real world, it is important to be aware of the many different views that one piece of information can present.

When presenting information, sometimes it can be shown in a particular light that whilst true may also be misleading. Have a look at the following graphic. Two distinctly different ways to present the item but both of them are true.

The same can be done with charts. For this blog post, we figured we would show you some light hearted visualisations.

Take a look at the following two charts. Both are reporting on the exact same set of data.

Kerry (yellow) is about half the value of Cork (red). However, by changing the 3D perspective of the chart, it is easy to manipulate how the chart would be perceived.

For this reason, we love critically examining charts and it makes our day when we come across one which is just so wrong!

Below are a few “inaccurate” charts that we thought were an interesting way to present statistics…

The following chart was used to present labour rates in the US…

If you look at the y-axis and then compare against the reported values, there is no correlation between the two. November has the lowest value at 8.6 yet is higher than Feb and Mar at 8.9 and 8.8 respectively. It is also higher than the axis 9.0 scale.

The next chart shows the breakdown of 2012 US Presidential Candidates…

Leading the pack was Palin followed by Huckabee and then Romney.

However, when one looks at the percentages it appears that the total breakdown which should be 100% is actually 193%.

Obviously a similar approach was used to poll Scots on whether they were for or against independence…

According to this image from imgur.com via reddit.com, most people feel that the A Levels are not getting harder…

Misrepresentation of the numbers may not be due simply to calculation errors. Sometimes chart designers choose not to represent all the facts. The following chart highlights the massive gulf between 35% and 39.6%…

On other occasions, the effectiveness of a chart may be due to simple errors. This example that caught our eye was down to the use of a map chart in the Wall Street Journal (a black & white publication)…

Closer to home, the following pie chart image was taken from one the website of our national papers during the local election tally count in 2014. Without examining it, one would be mistaken for presuming that all four segments were in or around the same…

But there’s five segments listed!?!?!?!

Finally, when preparing charts, be mindful of your audience and whether or not they can see the information…

For proper and accurate reporting of your data, give Killian or Conor a call on 01-2790020.

Sources:

  • http://www.businessinsider.com/the-27-worst-charts-of-all-time-2013-6?IR=T
  • http://www.statisticshowto.com/wp-content/uploads/2014/01/pie-chart-misleading.png
  • http://http://static.businessinsider.com/image/51bf0e52ecad04af6a000012/image.jpg
  • http://i.imgur.com/IiBzgdY.png
  • https://www.buzzfeed.com/katienotopoulos/graphs-that-lied-to-us?utm_term=.go2E0ML64j#.iq46j4VBX3
  • Mhttp://imgur.com/y9SzZaG
  • www.independent.ie
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