From the monthly archives:

August 2009

It’s very easy to use charts to support false arguments, distortions, omissions or outright lies. But you can use words and statistics too. If you want to deceive nothing will stop you. (Required reading: How To Lie With Charts and How to Lie with Statistics).

Simple lies are often easy to spot and not very interesting. More interesting are our biases. Germans call it weltanschauung (“world view”) and without it we wouldn’t be more than boring rational machines. Our biases help us to select the data and interpret it the way it makes sense to us, reinforcing our believes.

Lying with charts, if done properly (!), is more an act of omission (what you hide) than an act of commission (what you show). To better understand the differences, let me give you an example of how data visualization amateurs lie with charts.

In a post titled “charts can be deceiving”, E. D. Kain writes:

I’m not a huge fan of charts because I think they’re usually just used to create illusions and sales pitches.(…) Numbers don’t lie, but how we present them can make all the difference in the world.

Then he goes on and offers an example of how deceiving charts can be. I’ll recreate them for you. Chart A is the original chart, Chart B is his:

Jon writes about the flaws in both charts, so I’m not going to discuss them here.

It’s funny to see how a lack of action (the original chart accepts the Excel default scale) induces an over reaction (an absurd “theoretical” scale). Manipulating the y-axis scale is “How to Lie With Charts 101”.

Yes, charts can be deceiving. Words too. Numbers don’t lie? Bullsh*t. The political discourse is full of “illusions and sales pitches” and carefully selected and biased numbers. Yes, charts can be deceiving. It takes one to know one, I guess.

Deconstructing Lies with Charts

The original chart reveals a clear act of omission: how can you conclude anything relevant if you have no reference to compare the trend to?

So, let’s try to answer this question with the available data: are the wealthiest 1% of households getting a more favorable tax treatment, or not? First, we need some contextual data:

So, the wealthier you are the more taxes you pay; a downward trend is also visible across quintiles (although the highest quintile shows a slight increase over the last two years).

And what happens within the highest quintile?

Well, this is interesting: tax rates increased, but not for the top 1%. But the general rule is kept: the higher the income, the higher the tax rate.

What if we chart, not the tax rate but the change, assuming 1993=100? Again, some contextual data:

Tax rates for the lowest quintile declined sharply. And here is another general rule: the higher the tax rate, the less it changes.

Here is the detail chart for the highest quintile:

Well, it seems that at the very top some rules don’t apply, after all (surprise, surprise). The top 1% households did get a more favorable tax treatment after 1996, when compared to the top 5% and the top 10% households.

Takeaways

The world is never black and white, and your own shade of gray is as unique as your fingerprints. If you want to use charts to support your arguments, please don’t resort to scale tricks and make sure you add enough detail and contextual data.

There is no intrinsic objectivity in a chart, but if you want to support your story you should cover your bases and make sure it’s hard for someone else to come up with a different narrative. This is valid for charts but also for words and numbers.

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If you want to sell better data visualization practices you can’t use the same approach with everyone. Marketers use archetypes and like to create stories around them like if they were real people. Their marketing messages are then tailored for Jane (archetype #1) or Theresa (archetype #2).

Let’s try this. Allow me to introduce you to three of my co-workers.

Co-worker #1: Anna, a Newbie

Anna was asked to create a chart, something that she rarely needs to. After playing with the wrong Excel options, she comes up with a really ugly and inefficient chart (misconceptions about charts don’t help). I show her how a simpler one could solve several perceptual issues. She changes her chart but keeps some of the chart junk (she finds my chart too minimalistic and laments her lack of of graphic design skills).

Anna is now aware of what “data visualization” means – clearly more than creating a few Excel charts. She should work on her data analysis and communication skills and stop worrying about graphic design skills. Corporate culture and peer pressure will push her to the dark side chart junk side of data visualization. I hope this seed is strong enough to withstand it, but only time can tell.

Co-Worker #2: Peter, a Middle Manager

Peter agrees that some of our processes are terribly inefficient and wants to change them. We could try to improve data visualization, but that doesn’t make much sense if everything else remains the same.

I’ve been sharing some tips with Peter on how to create better charts and he starts to recognize a bad chart when he sees one. Problem is, his previous model (Excel defaults, PowerPoint templates) is shattered, but he is unable to create a new one. He feels lost.

My tips seem to make sense at the lunch table but when he tries to apply them something is missing. Tips have this effect on people: they create an illusion of knowledge but the lack of context renders them almost useless. He needs a crash course on information visualization.

At this level, we are not discussing how to improve a chart. Instead, we must discuss how to add best practices in information visualization to the data management model. Selling this to top managers isn’t always easy. But Peter likes to bang his head on a wall…

Co-Worker #3: Frank, A Professional Chart Maker

Frank creates presentation charts every single day. Ten years ago he was creating exactly the same charts, 3D effects and primary colors. He doesn’t recognize the problem and the audience seems to be ok with this routine. If he needs something a little more complex than 3D pies and bars his manager asks me to help. This could spark his curiosity, but it doesn’t.

I believe Frank will never try to improve his data analysis, management and visualization skills, unless he’s formally ordered to do so. He’s not dumb, he’s just a little too comfortable in his comfort zone.

It’s Your Turn

I want to add more details about Anna, Peter and Frank and I’d like you to help me. How do you see them? How are you going to sell them our product (better data visualization practices)? Would you like to add your own characters? An imaginary boss, perhaps? The IT guy? Tell us about them!

Photo Credit: Smaku

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You know, I would really love to quit my day job and spend my time learning about information visualization, write about it, help people understand why good information visualization skills are relevant for their business.

Now, I could try to speed up things by selling some crappy affiliate products, fill up the blog with Google ads or use some other “business model” internet marketers love. But that’s definitely not my model. I’m selling my Excel Dashboard Tutorial and writing an information visualization ebook. That’s what I like to do and that’s what I want to be paid for. And I’d like to promote good products (Jon’s Chart Utilities, Bonavista’s Microcharts or Tableau, for example) if I had the time to do it properly. But you’ll never see Google ads in my blog.

The Fart Machine

Displaying Google ads is a dangerous game that I don’t want to play. Here is an example. I was visiting an information visualization blog when I saw, right below the post title, a very visual “Online Fart Machine” ad (no, not the one above). I’m sure the blogger wouldn’t be pleased to see this kind of visuals in his blog, but that’s the risk of running Google ads.

This is what first time readers see when they arrive at your blog. It hurts your message, your credibility and probably your future income.

The Trojan Horse

It’s not the fart machine only. Since you have no or little control over Google ads, you may end up sending contradictory signals to your readers: you write about best practices, but your ads act like a Trojan Horse, advertising the worst possible practices. I see this all the time.

Premium Chartjunk

3D effects, backgrounds and shinny textures are well-known examples of chartjunk. I’ll call them the “regular chartjunk”. There is also the “premium chartjunk”. Every time you add clipart to your charts and presentations (because it’s funny or cute) you’re entering the realm of the premium chartjunk.

How can you avoid premium chartjunk? Remove any clipart and any kitten images and pictures and please, please, make sure you know what your audience defines as “bad taste”.

(And unless there is a very bizarre lateral thinking going on,  I’m pretty sure a fart machine will not speed up your promotion or bring visits to your blog.)

Photo Credit: Chris Devers

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