NYtimes.com - College Endowments Loss Is Worst Drop Since ’70s
NYtimes.com - College Endowments Loss Is Worst Drop Since ’70s
Remixed College Endowment Graphic
Remixed College Endowment Graphic

What Works

Stories like this one that cover a data driven report should always include an info graphic. But, of course, this is coming from an avid fan of info graphics. Kudos to the NYTimes for including a graphic and for including not only the punchline – the huge drop in college endowments in the very recent past months – but also some context about what college endowments were doing before. I would have liked even more context because fiscal year ’08 was already seeing some of the downturn in the market. Total movement for all endowments, or endowments divided into fewer categories, since ’00 would have been even better.

What Needs Work

It is intuitive to portray data that “drops” (according to the headline) or rises with the change along the y-axis. I did a little remix just to show you what I mean. In the first glance at the data, the increase or decrease is going to be more legible when it’s happening on the vertical axis. It’s just the way we learn to read charts and graphs. Before that, I suppose our tendency to associate the vertical axis with things rising and falling came from gravity. The laws of physics aren’t going to change – stick dropping/rising data on the y-axis until gravity causes changes in the x-axis.

The other thing I might have changed was the choice of categorization. What is gained by splitting the data into the uneven increments that appear here? First, increments should either be even or should have some reason for being uneven. We’ve got a $500m range, a $400m range, a $50m range…it’s all very unclear why these are the important categories, especially when there is no immediately obvious significant difference between them. They all seem to have been more or less flat in FY’08. Then they all plummeted ~21-22% between July and November of ’08. I would have opted for more historical context and fewer categories.

The Wall Street Journal is running basically the same story with a different graphic though they still stick with the horizontal arrangement. I like there’s even less because they

Relevant Resources

Katie Zezima (27 January 2009) Data Show College Endowments Loss Is Worst Drop Since ’70s at the NYTimes.com

John Hechinger (27 January 2009) College Endowments Plunge Wall Street Journal Online

National Association of College and University Business Officers 2008 NACUBO Endowment Study Available for Purchase.

Eye Color Map from Peter Frost (2006) via Beals & Hoijer (1965) An Introduction to Anthropology
Eye Color Map from Peter Frost (2006) via Beals & Hoijer (1965) An Introduction to Anthropology
Eye Color Map of Europe - In color!
Eye Color Map of Europe - In color!

What Works

Color works. It helps that in this case, the characteristic being mapped is eye color, so it’s kind of a no-brainer to shade the areas where blue eyes are prevalent in blue and the areas where brown eyes are prevalent in brown. Even if this graph were to be printed in a grayscale journal (which is probably why the one on the left tries to use hatching to distinguish the areas), using degrees of full shading is easier to distinguish than using hatching patterns. Most printers can handle printing 10% gray, 50% gray, and so on.

What Needs Work

The areas that need some work, even in the color version, are the areas between blue and brown. Right now, those areas are lighter blue and lighter brown. The problem is that because the blue is mapping directly to the characteristic in question – blue eyes, blue area – it’s easy to think that the lighter blue areas represent areas where people have really light blue eyes. But, in fact, those areas are full of a mix of people, some with light eyes, some with dark eyes. I might have gone with a staggered blue/brown pattern or just chosen a color that doesn’t have anything to do with eye color, like purple.

Relevant Resources

Peter Frost (2006) Why Do Europeans Have So Many Hair and Eye Colors?

Western Paradigm blog (February 2008) The Blue Eye Map of Europe [Note to Readers: I couldn’t find the original version of the color map so I am linking to the blog where I found it rather than the original source.]

Wired Magazine Features Infoporn - Playmates' Diverging Bust-to-Cup Size Ratio
Wired Magazine Features Infoporn - Playmates

What Works

This graph does a nice job of representing three different linear scales without having to be in three dimensions. Time is on the x-axis, as it usually is. Then we see cup size on the right y-axis and bust size on the left y-axis. These two measurements use quite different scales – bust size is measured in inches and cup size is measured in two different ways, both of which are mapped onto an equidistant lettered scale. The distance between an A and a B on the left y-axis is actually about the same (1″) as the distance between 33 and 34 on the right y-axis. If you were going to set up a similar graph, it would be important to maintain the ratio between the two y-axes measurement scales. In this case, the ratio is 1:1, but you could imagine that the same style graph would work if the ratio were 1:2 or 1:3, just about any linear relationship will do.

What Needs Work

I suppose it may be more risque, but it strikes me that the same information could be conveyed with more pizzazz if the relationship were communicated visually. Most people, women included, don’t have a good sense of just what changing both cup size and bust size at the same time is going to look at. Humans are good at perceiving symmetry and proportion. Thus, I’d rather see this information as a series of clay models than as a chart. Bottom line: the information is visual to begin with, we’re talking about the way playmates look, after all. So why translate visual data (the pictures of women) into a chart?

Relevant Resources

Katharine Gammon for Wired Magazine (2009) Issue 17.02 “Infoporn: Today’s Playmates Are More Like Anime Figures Than Real Humans”

Carol Rados for the Food and Drug Administration Consumer Magazine (2005) Making an Informed Decision About Breast Implants

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New Jersey Commission on Rationalizing Health Care Resources
Hospital Pricing Graph - SF Bay Area originally published in Health Affairs by Uwe Reinhardt
Hospital Pricing Graph - SF Bay Area originally published in Health Affairs by Uwe Reinhardt

What Works

This comparison is a fairly straightforward examination of the relative merits of tables vs. charts.  Both of these images are trying to help explain the tricky business of health care pricing.  The bar graph comes from an article in Health Affairs by Uwe Reinhardt that starts by taking a look at the cost of a single procedure across hospitals within a small sample of hospitals in the state of California.  The table does the same sort of thing but it was written by the New Jersey Commission on Rationalizing Health Care Resources so it looks at hospitals in New Jersey.  It also looks across a number of treatments, not just one.

Each of these presentation styles has its merits.  The graph is an instantly legible message:  the cost of a chest X-ray varies a lot from one hospital to the next.  The table doesn’t have the same instant legibility but it provides much more detail across a range of treatments, demonstrating that the pattern of discrepant charges is not restricted to a single treatment.  Further, the table demonstrates a pattern – the relative cost of hospital treatments is fairly stable.  If a hospital charges at the low end for one treatment, it probably charges at the low end for all treatments.

What Needs Work

The bar graph does a good job of providing instant legibility but it doesn’t give much detail.  It works in the introduction of the paper to orient the reader but would not be nearly as useful in the results section because it shows only one treatment.

The table provides a lot of detail, but unless someone is already deeply interested in the problem of health care costs, they may not take the time to read it. No patterns are immediately obvious – it’s just a boxy sea of numbers. The presentation of the table as a graphic does little to help the eye.  At least the columns are arranged from lowest payment to the greatest payment.  They might have been made more visually legible if the font increased or the boxes got progressively darker as payment values increased down the columns.

Relevant Links

Chaos Behind a Veil of Secrecy in Health Affairs by Uwe E. Reinhardt

How Do Hospitals Get Paid – A Primer” on Nytimes.com Economix blog  by Uwe E. Reinhardt

New Jersey Commission on Rationalizing Health Care Resources, Final Report 2008 by the State of New Jersey Department of Health and Senior Services