The massive burden of pie charts
9-9-9 data deserving a chart

Things they don't teach you at Harvard

Numeracy and graphics apparently are not on the syllabus at Harvard, if one were to judge from this chart from the most recent edition of Harvard Magazine:


I added the orange circle to show a typo. But pretty much everything is wrong with this chart, from the sideways labels to the redundant use of data labels, column lengths and axis labels to plot the same series of data. (See the posts on self-sufficiency.)

Meanwhile, the insistent printing of five digits for the dollar amounts and the academic-year styling of the years are giveaways for innumeracy: the reliance on precision where it is neither useful nor necessary. Nothing at all is lost by rounding the amounts or shortening the years.

Most worrisome is the defiant announcement that the data is "not adjusted for inflation". One might as well replace that with "this analysis can't be trusted". When plotting a long time series, there is no excuse for not adjusting currencies for inflation. A dollar in 2010 just does not have the same spending power as a dollar in 1986. This is not a mere oversight; it's a major blunder, as revealed by the following junkart version:


When the data is not adjusted, it appeared that tuition, room and board jumped by 220% between 1986 and 2010. However, when adjusted for inflation, the cumulative growth was only 75%. Without the adjustment, the reported growth was exaggerated threefold.


This is a good example to explain, yet again, why statisticians adjust data. The raw data is the blue line shown above. It shows the cumulative growth of 220%. This metric is misleading. One should ask: how big is this 220% growth, really? It should depend on how much more expensive other goods and services have become over the same period of time, shouldn't it? If the costs of groceries, clothing, fuel, etc. have all gone up by 200% or so, or if wages have also gone up by that amount, then the steep blue curve would not be so scary.

The green line is the raw data adjusted by the CPI index. CPI is the inflation index which, put simply, is the average price index of a basket of goods and services. So, the green line is how much tuition, room and board has grown after "controlling" for the growth of the average basket of goods and services; it's the "excess" growth.

Of course, the excess growth is what the chart should be portraying.


Feed You can follow this conversation by subscribing to the comment feed for this post.


Sorry, but the chart-maker clearly said that they hadn't "adusted" for inflation...;)


One might comment that all the extra meaningless stuff on the chart might be a metaphor for higher education itself, where we all managed to learn a lot of extra meaningless stuff.


One typical reason or excuse for not adjusting for inflation is that it is not always clear what is the correct way of adjusting, or if it is known, that the necessary data series does not exist (e.g., is the CPI index an/the appropriate base for taking out inflation from tuition, room and board?)

H. T. Reynolds

This graph does meet some standards (e.g. data to plot size), but I agree with the main point, way too much ink for the amount of data, redundancy, etc.


The fact is it is using data to mislead. Harvard over this period I belive has also significantly increased student aid. It would be useful to show both full Ron and board and what the average actually paid ECG year after need based financial aid.

Craig W

I think adjusting a time series for inflation is important, but I don't believe that makes the chart any more useful. Regardless of the whether or not it is adjusted, isn't the obvious question, "is that a lot?".

So why not include a a more relevant reference/adjustment... like the cost of other top-tier private schools? And/or public schools? I mean, so what if the cost of Harvard has increased by 220% if public colleges have increased 1500% over the same period of time? And wouldn't we feel moved by this data if the cost of Yale increased only 25% over the same period of time? Or 500%?

Or what if the average starting salary of Harvard graduates has increased 560% over the same period of time? Wouldn't that change the perception of the data?

Simply adjusting this data for inflation doesn't make the chart much better, but answering the obvious first question does.

The comments to this entry are closed.