Just as there are counterfeit handbags that look like the real thing, there are fake data graphics that look like the real thing. Reader San C. shows us an example of this (found on the All Things D blog here):
At first sight, this appears to be a bubble chart. Further, the legend is telling us that the colors are meaningful. So, the bubbles correspond to different types of data, grouped by color, and the size of the bubbles represents the relative level of concern expressed by respondents.
That would be true if we were looking at the "real thing". But this is a counterfeit. How do we know it's fake?
First, the size of the bubbles was not sized to scale. Just look at the Social Security Number versus credit card number (shown on the right). A 1% difference shouldn't be visible on this sort of chart but the credit card bubble is clearly smaller.
Second, the legend gives the impression that the tint of the color carries information. However, it really doesn't. I lined up all of the green bubbles in order of decreasing data, and couldn't find any pattern to the tints.
There also isn't a clear pattern in the location of specific bubbles. Were they randomly scattered onto the chart?
In summary, this is the ultimate non-self-sufficient chart. If we remove the actual printed data from this chart, we're left with nothing.
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This data can be put onto a grouped bar chart dot plot.
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Aside from the graphical aspects, we should pay attention to some statistical issues.
The article does not stress enough the potential bias of this survey. The survey is an online survey of Internet users. Their average opinion about Internet-related issues should not be used to represent the opinion of the average American without careful consideration. There is a good possibility that people who have concerns about Internet privacy are less likely to be found on the Internet.
I also wonder if survey takers understand clearly the poll question. What does it mean by a company "accessing my personal information"? Does it mean I give the company the information (such as my credit card number) because I need to complete a transaction? Does it mean the company purchases such information from an information exchange? And if so, with or without informing me?
In particular, I don't understand the 28% who say they are not concerned about companies accessing their social security number.
Long-time reader Omegatron tells us about this report card issued by ACLU on the liberal-ness of different potential candidates for U.S. President. (link to PDF)
Perhaps because the designer realizes what a mess this chart is, he decides to greet readers with the legend text, typically shoved to the sides of a chart. "Ratings are determined on zero-to-four torch scale." This leaves me scratching my head because I see flaming torches and I see black torches without flames. Is it really an 8-point scale with half points?
Eventually, I realized that the torches without flames are part of the background of this chart, they are just placeholders to tell us up to four points can be scored on each issue. We should really be counting the orange flames!
Or perhaps the designer is cleverly differentiating zero torches, which is a negative rating, from big question mark, which indicates the candidate has no stated position, thus no rating on that issue. Keeping those two situations separate is very important. In the following reconstruction, instead of filling all of the zero-rating boxes (for which there are many), I leave zero ratings blank but insert a gray box to indicate "no rating".
I haven't reproduced the whole chart with all the issues but you get the idea of where I'm going with it.
For those supporting liberal viewpoints, this is a deeply disappointing chart. It shows the Democratic President rates below some of the Republican (Libertarian) contenders on supporting liberal causes. It also says much that between Gingrich, Perry, Romney and Santorum, they accumulated a total of four points across all these categories, equal to what one candidate can earn in just one category. (This type of information becomes clearer when the candidates are sorted in a meaningful way, as opposed to alphabetical.)
The following two charts plot the same data, the yearly amount of rainfall in Los Angeles over the last two decades or so. (The original chart, on the left, came from the LA Times. Link here.) Why do they give such different impressions?
The left chart appears very busy despite the simplest data set, thanks to printing the entire set of 21 numbers, each to the second decimal point on the chart itself. The axis labels do not provide extra information when all the data has been included, and it is highly unlikely any reader of the newspaper requires precise measurements of rainfall.
Chances are the reader is interested in how the general trend of rainfall in recent years compared to the historical pattern. Credit the designer for pulling the relevant data, including the average, maximum and minimum rainfall on record. On the right chart, all three historical numbers are incorporated into the axis so that they could act as reference levels.
Not to mention the axes were switched to preserve the usual placement of time on the horizontal axis.
The bar chart emphasizes the absolute values of each rainfall amount while the dot plot displays the differences between each measurement and the historical average. On the right chart, it is easy to observe whether any year's rainfall is above or below the expectation. Over the last two decades, it appears there were about as many years above as below the average, and the overages and underages do not exhibit any clustering.
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From a Trifecta checkup perspective, we find that the choice of data is not attuned to the purpose of the chart. The right data has been collected; a small transformation would have made all the difference. The selection of the chart type also fails to address the purpose of the chart.
Megan McArdle (The Atlantic) is starting a war on the infographics plague. (Here, infographics means infographics posters.) Excellent debunking, and absorbing reading.
It's a long post. Her overriding complaint is that designers of these posters do not verify their data. The "information" shown on these charts is frequently inaccurate, and the interpretation is sloppy.
In the Trifecta checkup framework, this data deficiency breaks the link between the intent of the graphic and the (inappropriate) data being displayed. (Most infographics posters also fail to find the right chart type for the data being displayed.)
While I have often raised similar complaints in the past -- and my current stance is link to good infographics posters only (which explains their scarcity on this blog), one of the significant contributions of the infographics "plague" is the status-hiking of the story-telling perogative. Unfortunately, this plague is yet another case of elevating stories above the data, which (to a lesser extent) is a complaint that Andrew Gelman and I shared about the "Freakonomics" trend. (See here, and Andrew's further comments.)
This doesn't stop McArdle from adding her own contribution to the infographics plague... the poster shown on the right.
Do yourself a favor and read her post in full. Link here.
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