Wednesday, September 28, 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 not collect test scores from test-optional colleges, or those that are open admissions.)

Monday, September 26, 2016

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 instance, 9% of all college students enrolled in the US attend a community college in California; and another 4% at community colleges in Texas.  Keep that in mind as you look at this data.

Tuesday, September 20, 2016

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 well as city, state, country, and organization.  They're below, and I think they say a lot about our profession.  What the information says is up to you to decide.

If you want to interact, click on a first name, and the other views update.  See? Interactivity can be fun too.

A note about the data: I did only minimal cleaning on it; when 6,000 people enter data on a form, there are bound to be errors.  Chicago, for instance, is not in Bosnia-Herzegovina. And I'm pretty sure Beijing is in China.  I did not clean up names, so if you really think your first name is "Mr. Daniel" you miss out on a chance to be included with the other Daniels. And Daniel is Daniel, not Dan, so variations are not grouped together.

Have fun.  And tell me what you think the data says.

Thursday, August 18, 2016

Tuition and Income in the States

Whoa, you might say as you look at this. It's way too funky for me. That's OK; I'm going to show you a new feature in the data visualization tool, Tableau, that I use that will make this all make sense. Hang on.

I wondered: Do states with higher median income levels charge more for tuition?  So I began to explore.

On each dashboard, median family income is displayed on the top chart, and college tuition on the bottom.  The view starts with four-year publics, but you can change it using the filter. The first dashboard shows only the rank of the states, from 1 to 5, with 1 being the high value in each.

If you can't make sense of it, don't worry: Use the little box in the upper right hand corner to select any single state, and that state's data will be instantly highlighted on both the income and the tuition chart.  You can see where a state stands on both measures.

The second dashboard (using the tabs across the top) shows the actual inflation-adjusted values (that is, $57,894 dollars in median family income, or $11,592 of tuition, both set to 2013), but the ranks are also displayed.  Use the state highlighter the same way, and hover over the dot for details. Note on this income chart I've broken one of my cardinal rules by not starting the y-axis at zero, for the sake of clarity.

You can get a sort of affordability index by looking at income ranks in comparison to tuition ranks, and you can see trends in both over time by state.

What do you notice here?

OK.  So maybe that's too funky.  Here's the same view, colored by red (high rank) to blue (low rank). If you like the original, it's below.

Wednesday, August 17, 2016

How Many Colleges Are There, Anyway?

A note in response to some questions from IPEDS geeks and others:  My data selection was from 2014 IPEDS data.  I used Title IV participating, US only, all sectors except administrative units.  That resulted in 7,018 institutions.  My visualization shows 6,876 because there were 142 institutions with absolutely no data reported.  I should have defined in my original post.

Also, the selectivity bands are not defined: Cut points are at less than 15%,, 25%, 40%, 60%, and 75%.  All others are "Not selective/Open."

College. University.  We think we know what these terms mean, and yet, any discussion of colleges in the US invariably leads to someone saying, "It depends on what you mean by college."

For instance, there are about 6,900 post-secondary institutions in the US, but only 2,654 offer a bachelor's degree; they enroll 10.5 million of the 17.6 million undergraduates.

Of all the institutions in the US, only 293 enroll at least 15,000 undergraduates, but this small fraction of colleges enrolls almost 40% of the undergraduates.  Conversely, there are over 4,300 options that enroll 1,000 students or fewer, but collectively they enroll only about one million students.  Our nation's public community colleges enroll over 6 million students on just over 1,000 campuses.

This visualization should give you plenty of options to see the shape of the higher education industry in the US: Filter and select to your heart's content, and as always, reset using the controls at the very bottom.

What surprised you?

Monday, June 20, 2016

Public University State Tuition

Note: The visualizations are not optimized for mobile.  A desktop is recommended for best viewing.

From the annual College Board Trends in College Pricing comes some interesting data, which I've combined into one database for visualization, focusing on public university tuition for residents and non-residents.  This looks complex, but it's pretty simple.

The opening view shows six charts: 2015 tuition for residents; for non-residents; and the premium a non-resident pays (in sticker price) across the top.  On bottom are three scatters: Resident tuition as a function of state funding per FTE student; five-year, inflation adjusted tuition for residents and not residents; and funding per $1000 of personal income and resident tuition.  Of these, I think the middle is the most compelling: Note the states that have raised tuition faster for residents than for non-residents.

The chart starts with US Averages in red, against the states as gray.  Use the control in the middle to highlight a single state on all six views.  As always, hover over any point for details, and use the reset arrow at lower left if you get stuck.

Using the tabs across the top, you can navigate to the map view.  Choose any value at top right to display on the map.  That value is displayed on the state, and the tiles (representing the states) are color-coded.  Red is high; blue is low.  Click on any tile on the map, and a summary of that state appears at the bottom.

Would your state legislator find this valuable? If so, I'd encourage you to forward to her or him. Otherwise, leave a comment at the bottom, letting me know what you see.

Wednesday, June 8, 2016

Public Institutions and Low-income students

Note: Visualizations are not mobile friendly.  I recommend a laptop or desktop for viewing this site.

Someone asked me today about what I thought higher education's biggest challenge was, and I said college costs without thinking.  And a few hours later, I still think that, with a twist: College costs for low-income students, especially at public institutions who presumably have a primary mission of educating students of all income levels in their state.

To be sure, costs are too high at private institutions, and many of the trends you'll see here are carried over and amplified in the private sector; but private colleges and universities may exist for different reasons, and that can be hard to capture in a visualization like this.

There are two views here, using the tabs across the top.  The first is a scattergram, arraying almost all 660 US, four-year public colleges and universities that admit freshmen (a few are missing data).  The x-axis shows in-state tuition in 2013, and the y-axis shows net price for freshman students who come from families with incomes of $30,000 or less, and who are paying the in-state tuition, most of whom are presumably in-state residents.  The color shows the percentage of students enrolled who receive a federal Pell grant, a program for very-low income students.

Reference lines show the unweighted, institutional averages, which allows the creation of quadrants, roughly:

  • The upper right, or high tuition, high net cost
  • The lower right, or high tuition, low net cost
  • The lower left, or low tuition and low net cost
  • The upper left, or low tuition, high net cost 

Color here is important: Red dots are those colleges with lower percentages of Pell students; blue dots show higher values, although I've capped the color range at 40%, about the national average, if you include all types of institutions.  It's important because it shows how many students these institutions enroll, not just how well they do at reducing price (if they do.)  In other words, it's a bit easier to do a lot to reduce cost for students if you don't do it for very many; it's harder on your budget if you enroll more.

You can limit the view to states, regions, Land Grant status, or by using the filters to show only institutions with certain admit rates or Pell percentages.  As always, take a look at California.  Well done, California.

The second view shows in-state tuition over time, accompanied by net price for three groups of students who receive aid.  Students from:

  • Families with income of less than $30,000 (gold)
  • Families with income of $30,000 to $48,000 (orange)
  • Families with income of over $110,000 (the highest band reported in IPEDS).  This is in blue.

The bottom chart on the second tab simply turns these numbers into an Net Cost: Tuition ratio.  A value of 1.5, for instance, means that the net price is 1.5 times tuition.  Note the definition of net price:  

Net cost shows all costs associated with cost of attendance, minus grant aid.  For example, a university may have a tuition of $5,000, but a cost of attendance of $17,000 to include housing, meals, transportation, and personal expenses.  If a student receives $10,000 in grant aid, that student's net price is $7,000, which is greater than tuition alone.

As always, hover for details, and use the reset button at lower left if you get stuck. 

What do you see here?  What else would you like to see?

Friday, May 20, 2016

Changes in In-State Freshman Enrollment in Public Universities, 2002-2012

This is a good example, I think, of how data visualization helps you make sense of things: Even simple things like a small table of data.

In this case, the table is from The College Board, showing changes in the percentage of in-state freshmen in our nation's public universities.  You can see the raw data by downloading Table 28, here. What you can't see by looking at that table, of course, is the overall pattern.  That's where a picture comes in.

There are only two numeric values in the table: Percentage of freshman enrollment that are state residents in 2002 and 2012.  I added a third, by subtracting one from the other.  Then I put them on a choropleth hex map, a format I like because all the states are the same size.  On this map, orange colors show states where the percentage of in-state residents has increased; purple shows a decrease, and grays are mostly even.

Be careful about interpreting this data. This visualization does NOT show, of course, that a university system is enrolling fewer in-state students; in fact, the number could have gone up if non-resident enrollment also increased, but at a faster pace.  It just shows what has happened to the makeup of that freshman enrollment: More in-state (orange) or less in-state (purple).

What do you see?

Monday, May 9, 2016

New SAT Concordance Tables

Note: I tweeted a link that was set up for mobile, and thus the visualization scrunched down to almost nothing.  If the URL has m=1 at the end, just delete it, or click on the title above to go to the desktop/iPad version.

The College Board just published long-awaited concordance tables to compare new SAT scores to old, and new SAT scores to ACT.

You can download the data here if you wish, or look at them visually below.  The tables in the data correspond to the tables on the visualization (that is, for instance, that Table 7 in the College Board worksheet can be viewed on Dashboard 7 here, using the tabs across the top.)

For convenience, Old SAT scores are always in light gray.  Notice also I've labeled the chart when the axes are not synchronized.

As this data is public, I have cited the original source, its purpose is educational, and this blog is not monetized, I believe the use of it in this format falls under Fair Use.

As always, hover over the dots for details.

Friday, April 8, 2016

A Deeper Dive on The Coalition Data

There has been a considerable amount of discussion in the admissions world about The Coalition for Access, Affordability, and Success.  I remain skeptical about the motives behind this, as I did when I wrote this in the Washington Post.  To be clear, however, I believe colleges have the right to create their own admissions platform and conduct the business side of higher education with great latitude. I am merely questioning how a fractured admissions process helps low income students find, apply, get admitted to, and enroll in college; and the use of the term "access" by colleges who have, in general, poor records of providing access to low-income students.

Many school counselors I've talked to are very concerned by what they perceive to be a dearth of information about how this all will work, and there are also lingering concerns about privacy, which have not yet been publicly answered (to the best of my knowledge), even though one component of the application platform--the Locker--is scheduled to open this month.

These colleges represent the very top of the pyramid among private institutions, and also include many large, state flagship public institutions, as well as a few statistical outliers.  But to look deeper at the data, I downloaded a large IPEDS data set, and just scratched the surface.  What should jump out at you is the impressive list of colleges, their collective wealth, and position on several of the scatter grams, below.

Use the tabs across the top.  Every view has a filter to show public/private/all institutions.  Coalition schools are in red to make them standout; everyone else is in gray.  The universe is about 1,945 four-year, degree-granting, Title IV participating colleges and universities in the Midwest.US.  (corrected 4/17 at 6:32 pm CST).

What do you see?

Wednesday, March 30, 2016

The Boom in International Enrollment

You hear a lot about enrollment of international students these days, and often, I think, when a subject gets a lot of play, it tends to be overhyped, often by people who don't really understand the data.

This would not be one of those times.

I used IPEDS trend analysis to look at enrollment of non-resident students (that is, students who are neither US citizens nor permanent residents) over time.  For comparison's sake, I also looked at overall enrollment over that same time.

This data set includes all 7,276 post-secondary institutions in the US, both degree-granting and non-degree-granting, whether or not they participate in Title IV programs, so my usual advice about IPEDS data is amplified a bit here.  Still, the trends are interesting.

The blue charts (on left) show total enrollment at these institutions: Bars show numbers, and the line shows percent change since Fall, 2004.  The red charts (right) show estimated international enrollment.  It's estimated because I had to calculate it using two variables, and the "percent of students who are non-resident" is expressed in a whole number, which is less precise than I'd like.

Of course, you're probably not interested in all the institutions in the US, so you can use the filters at right to look only at certain subsets, in any combination: Large doctoral universities in the west, for instance, or baccalaureate colleges in New England.

If you reset all those filters (reset button at lower left), you can look at any college or subset of colleges by typing the name in the box and make your selection(s).  If you get in trouble, just reset.

What interesting trends do you see here?

Thursday, March 17, 2016

International Enrollment and Engagement

The world is shrinking, if not literally, then metaphorically.  Some colleges and universities embrace this in big ways, and this is the purpose of this visualization.

The Institute of International Education puts out good data on both international enrollment at US colleges and enrollment of US students in study abroad programs.  I've combined that data into two views that show both.

The top chart contains two sort-able and filterable bar charts.  It starts out sorted from large to small on the left column, namely study abroad students in 2014-2015; if you'd rather sort by total international enrollment, hover over that x-axis until the small icon pops up and click that.  Reset by using the button at lower left.

The bottom charts shows every college in the data set, with study abroad on the x-axis and international enrollment on the y-axis.  Each dot is a college, color coded by control.

As always, if you want to look at a smaller set of colleges, use the filters on the right.  They will control both charts at the same time.

Three things: First, the data are for all students, graduate and undergraduate.  The IIE data are not broken out, so it's not possible to determine meaningful percentages, except of course for colleges that only enroll undergrads.  Second, the data is only reported for colleges that enrolled 10 international students and/or sent 10 students abroad.  Assuming the colleges reported the data.

So, on that point:  I've checked this data where I seen anomalies; there are several obvious colleges where it's missing.  A final caveat: High numbers can be caused by lots of things, including location, wealth of the student body, and curricular offerings, among others. There is (or should be) no value judgment attached to the numbers you find here.

Thursday, March 10, 2016

Election Results with Census Data

I normally focus on Higher Education data on this blog, and in fact, this visualization started out as a higher education post: I wanted to look at presidential election results from 2012 to see if education played a part in how people voted.  But since I had a large census file anyway, with lots of interesting information like income, ethnic groups, and other data, I decided to take it one step farther.  OK, may steps farther.  And to me, almost everything is ultimately about education.

If you don't like to interact with these visualizations, stop right now.  You'll have to play with this to see how it works.

On the top view, you see every county as a dot, color-coded by region, and arranged on a grid.  Hover over any dot for details, if you'd like.  Counties voting more heavily for Obama are on the right; Romney counties are on the left.  Wealthier counties are on top (higher median family income), and poorer are at the bottom.  Note the reference line at $53,046, the national median.

If you want to look at a specific state or region, you can do that using the filters.  But you can also look only at counties that meet certain demographic criteria, of your choice.

For instance, you could find counties that are at least 15% Hispanic and where at least 10% of the adults have a Bachelor's degree.  Once you apply the filters, only the counties that meet those criteria are displayed.  Use filters in an combination.  (Of course, you can't find any county that's 51% White and 51% African-American; the filters aren't magic.)

The data also shows up on the map at bottom; it's pretty self-explanatory: Each county is colored blue (Obama won) or orange (Romney won.)

As always, the reset button is at bottom.

I find this very interesting, and I hope you do too.  And I hope you vote in November; I need you for my next visualization!

Saturday, February 27, 2016

My homage to the Atlas of the Census

In eighth grade, a teacher introduced my class to the Statistical Abstract of the United States, and it changed the way I looked at numbers and information.  Of course, in those days, it was just a book, and very hard to interact with.  But I still remember poring over it, absorbing interesting, if arcane, facts about the country and its regions.  Ever since, I've been fascinated with reference books like it.

Then, sometime about 2005, I came across the Census Atlas of the United States, and my mind was blown even more.  It contains page after page of maps, representing gobs of data, visualized in a way that tells stories, sometimes with a single picture.  One map, especially, made an impression on me. It's in this chapter, page 14 of the chapter, page 40 of the book, showing Prevalent Asian Group, by county.  If you can't download that large .pdf file, it's below:

In my job, and in higher education in general, we think about race and ethnicity a lot, of course, but here was something that exploded and challenged the status quo and made me think differently: "Asian," was not a monolithic term.  Far from it.

That day, I bought a copy of the Atlas, and always pick it up when I see it.  It's astonishing, I think, and I still discover something new every time I spend some time with it.

I've wanted to do my own mini-version for a long time, but the thing that makes it hard is getting at Census Bureau data.  It's either very hard to extract, or rolled up in ways that don't inspire further analysis.  But I did come across a file that was accessible and fairly easy to work with, with data on a lot of factors at the US county level.  And I started working on it.

This includes 19 maps: The first 16 show US counties, colored by the variable indicated.  In the heading is the US average.  For instance, about 66.2% of the US population is "White alone."  All maps are color coded with that center value as the center point.  Check the legend.

You can look at the whole US or just a state; unfortunately, adding Alaska and Hawaii makes it hard and time consuming to get the maps to look good.  If you have Tableau, you can download this and look at it yourself.

The maps have data filters on them too.  So if  you're looking at the view with percent of adults with a high school diploma, for instance, you can pull the slider up or down to show only those counties with very high or very low values.  On each map, I've also added a somewhat-random second slider, so you can see combinations of variables.  On the high school graduates one, for instance, you can also look at population density.  See which counties have high/high, high/low, or low/low combinations. Play around.

Additionally, there are three other views: Two showing 2012 presidential election results, and one scatter-gram, where you can cross any two variables, and see the relationships between them.

If you work in my job, you might find interesting data that can help you understand how--and why--your distant markets are different than your local ones.  Or maybe it's just fun to play with.

Either way, I hope you enjoy it.  I'd love to hear what you discover.

Thursday, February 18, 2016

Educational Attainment in the States

In case the coverage of the 2016 presidential election didn't convince you, this might help you see why people in the rest of the country seem different somehow.

The data are from the US Census Bureau's American Community Survey, in 2012; this shows the educational attainment of adults 25-34 in that year.  Use the control at top right to pick a value to display on the map, and the states (represented by hex boxes here) change color to show the value you've chosen.  The bar chart also updates.

There are seven values:

  • Less than a HS Diploma shows the percentage of the population in that state aged 25-34 that did not complete high school
  • HS Diploma or Less shows the number above plus the percentage of people who have just a high school diploma
  • Exactly a HS Diploma shows just that: Everyone who graduated from high school but did not continue
  • HS Diploma or Higher is the percentage with at least a high school diploma, including everyone who went beyond that
  • Bachelor's Degree shows people who have just a BA or a BS
  • Bachelor's Degree or Higher and Graduate Degree should be self explanatory
Once you make a selection, the map and the bar chart update; both are color-coded with blue numbers lower and orange numbers higher.  Be careful with this: With low attainment rates, blue is presumably better (at least if you work in higher education); with higher attainment rates, orange is better.  Hover over a state to see the value, or look at the bar chart at the bottom, which displays the same data in a different format.

You may notice the map style; this is the first time I've used it, and I like it a lot.  It allows you to see values on small states that would otherwise get lost on traditional maps; and it allows Alaska and Hawaii to display just off the coasts without a lot of effort.  But I'd like to know what you think about them, too.

Thursday, February 11, 2016

Graduation Rates by Selectivity: Freshmen, 2007

This is the second part of my visualization of graduation rates from NCES. Part I is right below this one, or if  you want, you can click here to open it in a new window.

People in higher ed, and especially in government, talk a lot about graduation rates, and the presumption is this: That graduation rates are something we credit or blame on the colleges; that is, something a particular college does determines whether or not its graduation rate is high.  If Princeton stopped caring, presumably, its graduation rate would collapse.

Well, maybe.  Probably not, though.

We can see that a single factor, such as percentage of students in the freshman class with Pell, or the mean SAT score, can predict with some precision the graduation rate of a college or university.  If you don't believe me, see for yourself.

There is some variation in rates of colleges with similar profiles, of course, and people believe--correctly, or incorrectly, I'm not sure--that this is the important difference, or the value added by the particular college.  Maybe, but given the percentage of variance explained by single variables, I'm willing to guess other pre-college characteristics explain a lot of that unexplained variance.  Even as dull an instrument as US News and World Report realized years ago that having more Pell students lowered your graduation rate, all other things being equal.

Which leads us to this: The entering freshman class of 2007, and their six-year graduation rate, broken out by gender, ethnicity, and the selectivity of the college. You can see the pattern: The more selective the school, the higher the graduation rate.

Consider this.  You are headmaster at a college where they only thing they teach is dunking a basketball.  At the end of the course of study, students are given a test: 100 attempts to dunk the basketball.  And your school has a dunk percentage of 74.3%, the highest in the nation, and far better than any other Dunking College in the US.  All the people in Tallsville, where you're located, are very proud of you, as you educate mostly local kids from Tallsville, named for the Tall family.

The next year, you get ten times as many applicants.  And, being a college that wants to turn out the best dunkers (it's in your strategic plan, of course), you are suddenly able to admit only the tallest applicants, with the biggest vertical jumps and the largest hands.  Using the same instructional tools you've always used, your dunking percentage skyrockets to 98.2%.  And next year, guess what happens to applications? And guess whom you select from that pool?

The nation's oldest and wealthiest colleges mostly had a head start of several hundred years on the rest of us. And in times when college was almost exclusively the bastion of wealthy, white men from the upper crust of society, they have long histories of turning out men who end up, not surprisingly, wealthy and white.

Their reputation ensures that their position in the market will be strong for as far as the eye can see, and will allow them to select only students who, albeit not always white, wealthy men anymore, are destined to graduate from college.  If you're a little less selective, you have a little less luxury of choice.  And so it goes.

There is, of course, nothing wrong with that.  But choosing a college because of its graduation rate is backwards: The college will select you based on your propensity to graduate. Ponder that.

Do you agree? Or not?  Either way, I'd love to hear from you.

Tuesday, February 9, 2016

Graduation Rates, Rolled Up

I like the NCES Digest of Education Statistics, but some of the reports they present are almost unusable.  If you've ever tried to visualize a report like this, you know what I mean.  If anyone from NCES is reading this, please help and encourage the good people there to put data in a cleaned, unformatted report.

But, on to the data.  This is pretty simple, actually, and it bounces off previous visualizations I've done that show graduation rates are as much an input as an output.  The data are presented in three views: Over time, summarized for a single year, and by institutional type.  Click on the tabs to see them all, and use the filters on the right to select subsets.  You may want to look at women, or Hispanic students, for instance, and you can do so here.

There are some interesting patterns here.  It's clear that women, across the board, have higher graduation rates than men; and that colleges are not serving African American men very well.

What else do  you see? Anything surprising? Leave a comment below.

See this, too, for another way of looking at college graduation rates.

Friday, February 5, 2016

In-state enrollment and Pell

A recent article in the Washington Post piqued my interest: Why the University of Oregon turned to neighboring states for students, by colleague Roger Thompson.

Some of this is no surprise, of course. I've been looking at NCES and WICHE data for years, and even visualized the latter to show how demographics will change enrollment profiles at colleges across the country.

Lots of publics realize this, and lots have attempted to enroll larger numbers and percentages of students from outside their states. There's more to it than population, however: It's one of education's worst-kept secrets that students who travel farther to college come from families with higher incomes (or vice versa, of course), and in general, so do students who cross state lines for their education. Public universities have discovered that high out-of-state tuition makes them less desirable, and so have recently adopted a revenue maximization model, often offering large discounts to non-resident students.  It's generally better to get 70% of $30,000 than 0% of $30,000, especially when resident students might only pay $12,500, assuming the enrollment boost is sufficient.

This is a natural reaction by the universities in light of massive state funding cutbacks.

To boot, wealthier students have higher test scores, on average, and at prestigious-conscious universities, this can be an added bonus.

The danger, of course, is that this might exclude lower-income in-state students.  So, I took a look at the two factors over time at about 550 public colleges and universities.  The visualization below gives you the option to compare any four institutions by choosing the ones you want from the individual drop-down boxes: Orange lines show percent of freshmen from in-state; purple shows percent with Pell over time.  In order to select a college, just click on the box and start typing any part of the name. If you want UC Santa Cruz, for instance, you'll get better luck with "Cruz" than "California."

I started with four at random.  Make your own set.

What do you see? And are you surprised?

Note: Since I posted this, a colleague has pointed out that the IPEDS data are not sufficiently granular to separate in-state and out-of-state Pell students, which would have been the ideal way to look at this.  And, in addition, I'll add that a university could a) increase the percentage of its state's HS graduates enrolling, b) increase the number of Pell students, and c) see the percentage of Pell students go down if the freshman class grew substantially.

Wednesday, February 3, 2016

Degrees awarded by Discipline, Ethnicity, and Gender, 2011 to 2013

This is three years of data from the NCES Digest of Education Statistics, breaking out all bachelor's degrees awarded by ethnicity, gender, and discipline.  For the sake of clarity, I rolled many of the disciplines together, and on at least one view, rolled up ethnicities into groups as well.

The first view simply takes a look at ethnicity and gender: What do Asian women, or Hispanic men study in college?  Eight views on one dashboard, showing some interesting stuff: 30% of Asian women study Science and Math, compared to just 9.5% of African American men.  Business always dominates with men, except Hispanic men.  Interesting.

Behold the power of DataViz.  This view is the exact same day, just shown a different way to allow you to get a comparative view.  This shows all ethnic groups in the data set, however, and the data in columns adds up to 100%.  So, for instance, in the very top left, of all degrees awarded to Asian women, 19.82% were in business.  The figure is 34.3% for nonresident (international) men.

The third view turns it all around. Here you can see all the degrees awarded in a specific discipline in those three years, and see how they were distributed.  For instance, of all the degrees awarded in Education, 65% went to Caucasian women; of all the engineering degrees, 8.3% went to Asian males.

The fourth view is a little more complex, and allows you to create your own view.  For each discipline shown, the colored bars add up to 100% for the groups selected.  At first, it's a little noisy: Both men and women, and all ethnicities.  But this is where you can get interactive.  Look at just Hispanic students, for instance, by de-selecting every thing else; or see just men, if that's what you want.  The bars will always recalculate, and the very bottom bar rolls up all degrees into one bar, for comparison.

What do you see that jumps out at you?  Let me know in the comments at the bottom.

Thursday, January 21, 2016

2014 IPEDS Admissions Data

This is always a popular post: Statistics on the entering class of 2014 at about 1900 colleges and universities across the country.  It's based on IPEDS data, which I downloaded from the IPEDS data center and conditioned.  The source file is here, if you'd like to do something with it yourself.

This year, NCES only reports test score ranges for those colleges and universities that require tests for all applicants; in some regard, this makes sense, but it's unfortunate.  At my institution, for instance, about 94% of enrolling students submit tests, and this data might be helpful to students who do plan to apply with tests.  I plan to let NCES know this was not a good idea, and you can, too, if you'd like.  For now you'll know why these colleges don't show up.  You'll have to check with the colleges themselves.

This view starts with private, Liberal Arts Colleges in the Great Lakes region, but you can make the list be whatever you want using the filters across the top.  Be aware that if you select "New England," for instance, you can't then select "Florida" until you re-set the region filter.

The views from the top down are:

  • Admit rates, with the overall rate on the left, and men and women on the right
  • ACT Scores, at the 25th and 75th percentile
  • SAT CR Scores, at the 25th and 75th percentile
  • SAT M Scores, at the 25th and 75th percentile
You'll have to scroll down to see them all four boxes, and within each box, use the scroll bar.