## A Quick Guide To Lying or Misleading Graphs

Lying or misleading graphs are fairly common out there on the internet, even if they don’t use any false numbers or statistics. As most of us have heard the saying that numbers don’t lie, they can be presented in such a way so as to give a totally different impression than what the reaction actually is.

And misleading graphs are the best way to achieving this. Graphics are a great way to helping us visualize what certain numbers and statistics say. But because of this awesome potential, some people use misleading graphs to distort those numbers, while still being technically true.

Chiqui Esteban, the Deputy Director for Art, Maps, and Graphics at National Geographic magazine, has compiled a list of five ways graphs can be misleading or downright lying, even though they are showing us real statistics.

#### 1. BROKEN SCALES

These two graphs here are the exact same thing. The only difference, however, is in the way that they’re represented. Both of them show a slight decrease in the unemployment rate in the US between January 2014 and May 2015. But the graph on the left depicts dis drop in a more dramatic way than it actually is, leaving us with the impression that something greater has happened than a drop in unemployment from 6.6% to 5.5%.

The same thing applies to the above bars. Since they don’t show the full context, which in this case is the percentage both teams have in common – which is everything going from zero to .424 – then it gives the impression that the NY Yankees are far more successful than the Boston Red Sox, as can be seen in the left-hand chart. The reality can, however, be seen to the right.

In other words, the wrong graphs here are actually a good representation of things taken out of context.

#### 2. APPLES-TO-ORANGES COMPARISON

We sometimes find these charts depicting two, seemingly related topics and placing them together. The problem with these misleading graphs is that they give us a false impression about what’s happening. By looking at the graph to the left, we could say that at some point, the GDP plummeted as compared to the unemployment rate, after which it went above it. But the thing is that this comparison makes no sense. Is like comparing 150 pounds to 5 feet 3 inches and deciding which is bigger. There can be a correlation between the two, yes, but they are not two similar things that can be compared in this manner.

#### 3. CORRELATION CAN IMPLY CAUSATION

Similar to the point made above, this chart places two statistics together on the same chart, implying that the two things are connected and influencing each other. But the fact of the matter is that there’s no evidence that these two things have any correlation and there is no good way of representing them. It’s like showing a graph of the number of cars being sold in a year and overlapping it over another graph showing the of children being born during that same timeframe, and implying that there’s something there.

#### 4. IGNORING POPULATION SIZE

When talking about statistics which involve the population in some way or another, it’s imperative to actually take into account the number of people living there. Like this graph above can attest. While the graph of the left shows us which cities had the most murders overall (and saying that they’re the most dangerous), the graph on the right shows us the number of murders per capita, or in this case per 100,000 people.

And as you can see, the results aren’t the same. It’s only logical that a larger city will have more of anything than a smaller one. But that doesn’t necessarily mean that, if they were the same size, the results would be the same. This means that, even though the graph on the right shows Chicago to be the most dangerous, you would actually have a higher chance of being killed if you were in Detroit, New Orleans, or Newark (making them, in reality, more dangerous.)

The same thing applies to pollution and countries. While China does, indeed generate roughly two times more pollution than the US – when broken down in terms of actual population, it turns out that the average American is responsible for more than twice as much pollution than the average Chinese citizen.

#### 5. DECORATION CAN BE DECEIVING.

At first glance, these two charts are exactly the same, with the only difference being that the one on the left is in 3D, while the one on the right isn’t. So, what’s the problem here, you may ask? Well, in terms of the pie’s actual surface area, the green area in the left pie is actually bigger than the blue one. If the percentages weren’t there, then one would assess that the green part is bigger. With the percentages present, however, the difference between the two is subconsciously lessened.