How the Common Data Set Can Help You Determine Your Admission Odds

Although you won't find a crystal ball that can allow you to determine whether you will get into your top college choice, there is a little-known set of data that could possibly shed some light into how you may stack up in the admissions process: the Common Data Set. Each year, many colleges fill out a standardized questionnaire from the College Data Set Initiative, an effort aiming to help improve the quality of institutional data available.

Within the Common Data Set, you'll find information that could be helpful in determining whether your stats and characteristics line up with the data from students who were admitted during previous cycles. In addition to finding out the average test scores, acceptance rates and ethnic backgrounds of admitted students, you can also find other unique facts that you may not be able to get anywhere else, and that you never knew were available, such as whether the college uses a waitlist or allows you to defer admission.

"I use it to illustrate to students how to find out if colleges consider demonstrated interest in their admission process," says Evelyn Jerome-Alexander, founder of Magellan College Counseling. She explains that there is a chart within the Common Data Set where colleges share which factors they consider in the admissions process and how much weight they give to that specific factor.

"The chart is useful also because it tells you everything they consider, and it tells you the strength with which they weight each of those items. It helps students see, for example, especially with the highly, highly selective schools, that GPA and test score are always going to be in the 'very important' category, but you'll also see that many of them strongly consider leadership, and not just the activities that students do, but the depth to which they do them, so you can see how colleges really are evaluating students."

For instance, if you review Princeton University's most recent Common Data Set, you'll find the following chart, which shows that extracurriculars, talent/ability, character/personal qualities, recommendations and essays are all listed as "very important" in the evaluation process. The weight of these pursuits match that of class rank, GPA, test scores and rigor of the secondary school record, as shown:

Find True Diversity Stats

Another way the Common Data Set can be useful is to help you determine the reality of the diversity at a particular school.

"Colleges talk a lot and they put lots of great pictures up on their websites about their commitment to diversity, but the Common Data Set is where you find actual numbers. If I have a student for whom diversity is truly important, the Common Data Set is where you can actually find if a college is really hitting the benchmark that their PR campaign wants you to believe they're hitting," says Jerome-Alexander.

Get the Scoop on Required Courses

In addition, you can find out which prerequisite courses are required by a specific college, and how many of those courses you should take in high school if you want to attend that school. This can be very important if you have a target school in mind and you're planning out your high school schedule.

For instance, New York University's Common Data Set shares the following for its required and recommended courses:

Not All Colleges Participate

Nina Berler, founder of unCommon Apps, says that while The Common Data set can be a very useful tool, not all colleges participate, and some that do don't publish the information on their websites. "Students should always check the date on the Common Data Set and realize that numbers vary from year to year," she advises.

Berler says that the Common Data Set can be particularly useful in three specific areas:

• Precise acceptances — overall and by gender
• Movement from the waitlist
• Importance of academic and nonacademic factors.

Learning how the waitlist moves can be especially useful to many students. "This is so very important because students often carry false hopes about the waitlist outcomes," notes Berler. "It's amazing to see how large waitlists are relative to the number of accepted students — not to mention how few may get off waitlists."

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