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    Outcome Reports - Understanding the Test-Optional Detail by Plan Type report

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    • High School subscribers who have used flags to tag all students in the most recent graduating class who did not submit test scores with their applications.

     

    The Test-Optional Detail by Plan Type report enables you to see the impact of test score submission on admission results by the institution.

     

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    For each test-optional institution, Test and No Test profiles are provided for enrolled and admitted students from the most recent graduating class, as well as for admitted students by plan type.

    This report helps answer two questions:

    • Is there an admission rate advantage for applying with a test score?
    • If an advantage exists, is it material?

    The first question is answered simply by comparing Test and No Test admission rates. The second involves considering data points and differences in the Test and No Test applicant pools, many of which can be assessed in this report.

     

    EXAMPLE

    Let’s take a look at results for enrolled students in the above example:

    Looking at the overall results to the right, we can see that a total of 39 students applied to NYU this past cycle. A total of 9 were admitted, resulting in an admission rate of 23%. The GPA range for the mid 50% of enrolled students was 3.49 - 3.59.

    Looking at the Test and No Test results, we see that out of the 39 applicants, 24 of them (62%) submitted test scores and were admitted at a 25% rate, while 15 did not submit test scores and were admitted at a 20% admit rate.

    On the surface, this suggests most applicants submitted test scores and were admitted at a slightly higher rate.

    That said, it’s critical to dig deeper to understand why. Is the advantage truly there, or is something else happening?

    There are four checks to confirm an admission rate difference is material:

    • There are sufficient data points. Be sure there are enough data points to draw any conclusions and that you understand the sensitivity of the data. Even with 39 applicants in our example, an increase of just one admitted student to the No Test pool results in a 5% increase in admission rate and negates any advantage for submitting test scores.
    • The applicant pools are academically comparable. A difference in admission rate may also be due to the quality of the respective applicant pools. For example, the test-optional pool may be weaker. In our example this doesn’t appear to be the case, as the GPA ranges for those with and without tests appear fairly similar. Note: for added context, we’ve provided the unsubmitted test score ranges for admitted students who applied test-optional.
    • The applicant pools have a similar mix of ED/EA/RD applicants. You should also confirm that the difference in admission rate isn’t impacted by how the applicants applied. For example, a reason for the difference may be that 100% of the applicants with test scores applied Early Decision and 100% of the applicants without test scores applied Regular Decision. In our example, about 33% of each pool was admitted Early Decision, so this isn’t the case.

    • The applicant pools have a similar mix of hooked applicants. The final reason for differences may be due to the mix of hooked applicants in each pool. This is not addressed in the report, so you’ll need to consider whether the presence of hooked applicants in the Test or No Test pools unduly influenced results.

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