Skip to main content

Important Notes

The work here is all mine; my wife tells me I occasionally make mistakes.

This is for informational purposes only, and although I believe what's represented here reflects the original data, there may be errors in my calculation or visualization, or in the original data itself.  I almost always link to the data source, and there are often disclaimers there, too.  Be sure to check them out.

Don't make any bar bets--or worse--strategic planning decisions based on what you read here without verifying the information for yourself.

This blog uses data from several sources.  Each has advantages and limitations.

IPEDS: The Integrated Postsecondary Education Data System.  I mostly use the IPEDS Data Center. Colleges and Universities that receive Title IV funding are required to submit data annually to IPEDS, which means you can find information on almost any college you're interested in.  Unfortunately, the data is not adjudicated, and it's obvious that the surveys for some smaller colleges are completed by people who don't understand the business or the information system they're using.

Additionally, surveys lag reality; the enrollment data for fall 2013, for instance, won't be available until sometime in summer or fall 2014 (in a good year); finance and financial aid are a year behind that.

Newbies to IPEDS find the site hard to work with, and I agree.  But overall, the amount and quality of data makes the effort worth it.

NCES Digest of Education Statistics: I first found this resource in the mid-1990's and it has saved my bacon a couple of times.  Good, summarized, and often longitudinal data about all levels of education in the US. These are pre-formatted reports (designed to be printed) and are nothing short of horrible to use with a data tool.  But when the information is good, it's worth it, even though you'll probably spend 95% of your time just getting the data right and clean.

College Board Trends in Higher Education: Good, summarized data on a wide variety of topics including pricing, aid, access, and outcomes.  Compiled from reliable sources by good data people, this information is usually downloadable in Excel but has some of the problems of the Digest when you try to make it ready for data visualization. 

IPUMS: The Integrated Public Use Microdata Series uses US Census Bureau data from the American Community Survey to provide astonishingly detailed data at the granularity of a single person.  Samples run from 1% of the population to 5%; and from one to three years.  Big files, and a bit hard to tackle, but really good stuff if you want to dig deep and ask complex questions of the population.

WICHE: The Western Interstate Commission for Higher Education publishes a lot of studies and white papers on best practices, but the most important thing they do is their "Knocking at the Door" projections of high school graduates looking forward by a decade or more.  It's not user friendly, but I've downloaded and combined the files into this visualization.

Data-dot-Gov:  This site has loads of good data (or links to it), some of it related to higher education.  You can spend a lot of time getting lost in this site, looking at things like FAA Investigations, locations of military veterans' grave sites, or "milk."

My Favorite Tool: And finally, the tool I use is Tableau Software. It's designed to allow even non-technical people the ability to ask questions of their data, and to get insight very quickly.  I almost always put the source of the data I use on my visualizations (or at least in the body of the blog post), and I encourage people to look at the NCES table, for instance, and the visualization to see which makes more sense.  I hope I'm successful in turning some data into insight.

You'll find the Tableau Community to be very smart, engaged, helpful, and encouraging as you try to make some sense out of your own numbers.  There are free versions of the software available, and you can publish your work to a public server to share with the world, and embed your visualizations into many blogs, including, obviously, Blogspot (Wordpress, not so much.)  

I consider myself a Tableau Dabbler, or perhaps an advanced beginner, very cognizant of my own limitations, but I'm happy to help any way I can.  Just drop me a note or give me a call.


Popular posts from this blog

The Highly Rejective Colleges

If you're not following Akil Bello on Twitter, you should be.  His timeline is filled with great insights about standardized testing, and he takes great effort to point out racism (both subtle and not-so-subtle) in higher education, all while throwing in references to the Knicks and his daughter Enid, making the experience interesting, compelling, and sometimes, fun. Recently, he created the term " highly rejective colleges " as a more apt description for what are otherwise called "highly selective colleges."  As I've said before, a college that admits 15% of applicants really has a rejections office, not an admissions office.  The term appears to have taken off on Twitter, and I hope it will stick. So I took a look at the highly rejectives (really, that's all I'm going to call them from now on) and found some interesting patterns in the data. Take a look:  The 1,132 four-year, private colleges and universities with admissions data in IPEDS are incl

Yes, your yield rate is still falling, redux (2021)

I've been creating this data visualization, or some form of it, for several years now .  I think it's most useful for higher education enrollment professionals who have to explain to people at their university why their yield rate is falling.  The short answer is that applications and admits are increasing faster than student populations: If a student today applies to an average of seven colleges, compared to four colleges twenty years ago, yield rate almost has to go down.  I'm sure AI will fix this, and all our problems, very soon. But I've spoken to others who use this other ways: To work with students to talk about chances for admission; to show parents how things have changed in the past twenty years; or to help journalists understand the lay of the land.  Whatever you use this for, I hope it's instructive, and I hope you feel free to share it widely. And if you work in a college or university and save yourself some time by using this, or if you work with clien

Freshman Migration, 1986 to 2020

(Note: I discovered that in IPEDS, Penn State Main Campus now reports with "The Pennsylvania State University" as one system.  So when you'd look at things over time, Penn State would have data until 2018, and then The Penn....etc would show up in 2020.  I found out Penn State main campus still reports its own data on the website, so I went there, and edited the IPEDS data by hand.  So if you noticed that error, it should be corrected now, but I'm not sure what I'll do in years going forward.) Freshman migration to and from the states is always a favorite visualization of mine, both because I find it a compelling and interesting topic, and because I had a few breakthroughs with calculated variables the first time I tried to do it. If you're a loyal reader, you know what this shows: The number of freshman and their movement between the states.  And if you're a loyal viewer and you use this for your work in your business, please consider supporting the costs