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Showing posts from September, 2016

Test score distributions, 2014

We tend to think a lot about a college's average test scores, despite the many ways colleges can and do manipulate them for their own benefit.  After my last post on the relatively low number of students who enroll in the most selective institutions, someone asked if I could do the same for test scores.  So here they are. I've calculated very close mean ACT Composite and SAT CR+M means by taking the midpoint of the 25th and 75th percentiles.  They're almost certainly not perfectly accurate, but are very close, in all probability.  Then I've broken up enrollment to show where students attend college. The first view is based on the earlier visualization; the second is a scatter showing both the ACT and SAT averages.  The first has just three filters; the second has more, plus a "Color By" parameter that allows you to color the colleges by one of several factors. I hope this helps people think about and put score ranges in some context. (Note: IPEDS does

All the fuss, updated

One of the very first posts I did on this blog was showing just how many "Uber Selective" colleges and universities there are (or aren't), and how many students they enrolled (or didn't.) I used it last week at a presentation at NACAC , and several people asked me if I had an update on it, so as soon as I got home, I pulled down the data and started visualizing it.  It's below, and it should be self-explanatory: Of the 1,943 four-year institutions shown, only 18 admit less than 13% of freshman applicants.  These institutions (blue bars) enroll just 82,000 students (under 15,000 of whom are African-American, Hispanic, or Native American), and only about 18,000 freshmen.  Yet they get a relatively large share of the press and attention whenever the discussion turns to college admission. This has limited interactivity: You can choose region, public or private, or Carnegie group. And of most importance: This is but a sliver of American higher education; for ins

Who's Going to NACAC?

One of the things I hope to show people on this blog is that data is a lot more fun and interesting when you actually do something with it , rather than just present it in a spreadsheet. Here's a good example. This week, over 6,000 people who work in or around college admissions will converge on Columbus, Ohio for the NACAC Conference .  (Yes, Oktoberfest is also in Columbus this weekend , and based on my informal discussions, there may be some overlap.)  NACAC puts its attendees in a table on its website for anyone to use. But it's just data: What does a simple spreadsheet have the power to tell us?  Maybe more than you think.  Yesterday, I put the information in a visualization (first page is set up for mobile but autosized) designed to help people find other attendees.  As a side effort, I put up a chart of the most common first names of attendees, and it proved to be very popular. So last night I did a little more, and looked at most common first, and last names, as we