Readers weren't confused by the overly precise graphs, we were confused by the entire premise of the macroeconomic Monte Carlo article.

And they weren't angered because of misconstrued intent, but because it was stated that anyone who supports basic income "borders on innumeracy", and the claim was backed up by a toy simulation that addressed roughly none of the potential effects of that policy.

The article also attempted to reduce the concept of policy debate into a STEMlord "show me the code or you're wrong" absurdity.

Obviously though, the author has learned his lesson. His lines weren't squiggly enough.

This reminds me of my favorite Java project, designed to make work-in-progress programs look exactly that to non-technical stakeholders who otherwise assume 90% complete UI means 90% complete application.

http://napkinlaf.sourceforge.net

One thing you may want to try, if you're not doing this already, is to remove the actual numbers on the axes when you xkcd-ify graphs. I think people see the numbers and think that the results are precise and removing numbers that mean very little can have a pretty big effect on people's perception of the precision of the results. I say this because your first example still has the numbers on the axis ticks.

This guy links to: http://matplotlib.org/xkcd/examples/showcase/xkcd.html

I've been in the matplotlib site a few times before and I noticed that the logo was weird. Turns out the the matplotlib website has a mode where all examples are rendered with xkcd, all text is converted to Comic Sans and all other sort of funny things happen. You just have to add the xkcd keyword in the url.

Here's another example of a documentation page completely unrelated to xkcd.

Original Style: http://matplotlib.org/examples/lines_bars_and_markers/line_d...

xkcd style: http://matplotlib.org/xkcd/examples/lines_bars_and_markers/l...

Those graphs look hideous. The wobbles are too big, and too regular.

Compare with an actual xkcd graph: https://xkcd.com/1306/

The author is conflating two very different issues:

1.) Imputing the imprecision of a mathematical model through stylized graphs.

2.) Choosing a firestorm of a political topic to demonstrate mathematical modeling.

A long time ago (by internet standards), Joel talked about that too in the context of software development, how appearance convey some degree of completion to people who can't see inside the source code. This led to this: http://napkinlaf.sourceforge.net/

Ironically, I trust Randall's graphs more than any professional-looking graphic in a newspaper or magazine.

I think instead of error bars, one could use blur to describe error http://blog.velir.com/uncertainty/index.html

I love it! I heard about this years ago and I think it's a great way to fuzz 'the science' and make it easier to think about. Look at it like this, as a 10 year old, you look at these graphs and see someone that can draw just like you. If you look at a graph of straight lines and precise blues and boxes and stuff, you get discouraged and think you'll have to work really hard for a long time to get to making computers do that.

Also this comic is somewhat related too: https://xkcd.com/1133/ If you can't figure out a way to relate your ideas in those 10 hundred words, you aren't thinking clearly enough. To help, here is the list of words: http://splasho.com/upgoer5/phpspellcheck/dictionaries/1000.d... and here is a checker for you to proof against: http://splasho.com/upgoer5/

I'll admit to having a similar strategy for mechanical drawings. I once discovered by accident that if I drew a pencil sketch, the machinist would understand that I wasn't asking for super precision, and I'd get a satisfactory part quickly. Or they would call me and ask: "Can I make it this way instead" or even "what are you really trying to do?"

Pretty sure that's why Balsamiq mockups look they way they do. Same principle.

I love this use case. This is also why I always make wireframes in black and white, and also keep them chunky. This automatically lets the viewer know that it's not a final mockup, and that they should comment on the high level UX rather than nitpicking on pixels.

I totally agree. This is the way most of economics is taught; concrete numbers provide evidence for ideas/models, but when learning their concepts, they simply slow you down.

Those graphs he converted into xkcd style are bad examples. Almost all the xkcd graphs I remember reading are illustrations for simple concepts. Well, let me put it this way. The graph is usually compact, small and a few simple annotation/caption attached to the graph. That's exactly why the xkcd example in the article works well. Try to scale this up to a large graph like the one author did. The curly lines just hurt my eyes.

I like the general direction of this thought. Some things are hard to communicate from a cold start. You need to already be thinking in certain terms in order to understand. Probabilistic ideas and arguments are often like this.

An interesting example is science and scientific methods. Something starts as a theory (eating fat makes you fat) and accumulates evidence for and against it. Evidence "against" the theory doesn't necessarily outright disprove it. It just weakens the claim in different ways. It can lower the probability that it is true (maybe it just seems like eating fat makes you fat, but it really doesn't). Sometimes the magnitude is smaller (eating fat makes you a little fatter, but not much). Sometimes it's kind of true, but the whole story is more complicated and the statement in the their theory needs to be made more precise (increasing fat consumption makes you fatter if everything else stays the same, but it also makes you feel full which makes you eat less of other things the effect only exists in controlled conditions).

The above example needs to be considered from multiple dimensions. People who haven't been thinking about this as a multidimensional thing have a hard time evaluating your statement in this way from a cold start. Experts used thinking the way they are explaining things think the public is stupid or uninterested. Even if they humbly agree that the public are just not experts, they still conclude the same thing. The public want everything boiled down to a simple statement that hides the texture.

X Causes Cancer

This KXCD style graph subtly conveys a little of that texture. I think this is a good thing. I really like XKCD. It's very good art for a very interesting definition of the word art.

I found myself conditioned to check for alt-text on all the xkcd-style graphs.

So authors: Another plus is that you can include a humorous caption for your graphs. I'm sure there's always a funny angle that you wish you could include but that wouldn't be an official part of the paper ...

I like this - it reminds me of advice when creating an early stage prototype: the higher the fidelity of the prototype, the more chance that your audience will think it is a final (hence set-in-stone) product.

I'd like to point out that there has also been some research done in order to see how to exploit these sorts of "sketchy" visualizations for information visualization. This paper by Wood et al. contains some very nice examples, as well as small user study:

http://openaccess.city.ac.uk/1274/

They show that users can judge the degree of "sketchiness" on an ordinal scale but that the judgement varies extremely between individuals.

I've done a Google Ngrams API that generates plots in XKCD style here:

https://github.com/econpy/google-ngrams

and a webapp version with slightly more advanced XKCD tweaks here:

http://xkcd.culturomics.org

Everything starts with matplotlibs xkcd lib but has been tweaked to produce plots based on the output of the Google Ngram Viewer.

I would have went with a squiggly line showing instead of a squiggly-histogram for full effect, but otherwise I think this is genius. Showing people information which is "correct" for all ways that information may be consumed is a critical skill these days, you cannot blame the reader and still be an effective communicator.

If you're looking for a UI mockup tool with support for back-of-the-napkin style drawings, I'd recommend the Pencil Project [0]. It's easy to use, open source and available on every platform and as a Firefox extension.

[0]: http://pencil.evolus.vn/

The biggest difference I see between the original plot and the xkcd() one is labels! In your article, there are no labels on the axes. Thus the numbers are context-less -- providing labels (and perhaps adding text at particularly important points) is more important the actual style.

Hand draw them using something like Paper by 53 on an iPad, or even in Paint...then they have the right essence of looking hand drawn (?messy) and people don't ask the question. And tbh, probably take less time as well.

I would be an interesting challenge to automatically generate XKCD graphs from real data (simplify, exaggerate, render as hand-drawn etc) in the same spirit as non-photorealistic rendering.

I must say that this post was quite convincing. However, I wonder if that really is Max Planck in the comments. If so, then I'm far more inclined to heed advice from him.

I think the graph has opposite effects to avid xkcd fanboys.

Balsamiq is great for this.

April fools?

Not a fan.

There is already a way to communicate imprecision of results.

Error bars

Error bars

Error bars

Error bars

Got it?