Hi! I’m a bit obsessed with Naviance, but I keep returning to the data sets for two schools (Brown and Kenyon). It would be helpful if anyone well versed in the ways of Naviance could help me draw some conclusions re: trends of accepted applicants from these two schools, if any exist. Thanks!
Have you looked at the graph function too? Sometimes that’s easier for me to interpret - you can see on a graph how you compare to other kids from your school.
Your data didn’t paste well but I’m generally familiar with the format. Brown is clearly higher SAT and GPA from your school. Focus most closely on the average accepted number for both SAT and GPA, not average applied number.
It looks like there is a clear track record and history with Brown, both in acceptances and kids attending. Kenyon it looks like they give one or two offers a year but few go there. SAT is not too high on average for Kenyon acceptances.
I would just caution against reading too much into Naviance GPA and SAT averages. In particular the common app has really increased applications over the last 8 years and the chart function may show you acceptances in your “circle” that were from 7-8 years ago. Things have changed so much since then that you really cannot use this data as an indicator of your chances.
Depending on your school, you also need to take a close look at the graph to see if schools are taking a wide range of students and bringing down the averages. For example, at my Daughter’s school, Williams and Amherst have accepted averages of 93/2050. But both schools took a few students with 90 GPAs and sub 1800 SATs so these are likely athletes or some other hooked student.
I think if you are in the range for a cluster of acceptances on a naviance graph you are probably ok, but you should probably hold off on buying that Brown sweatshirt until you actually get it.
(sorry just noticed that your data isn’t that old, but the point still stands, to a lesser extent)
You can use the tag [ code] data [ /code] to wrap around your data and it will be easier to view. Just remove the spaces inside the [ ]
If the kids from your highschool getting into selective colleges tend to have hooks like legacy, athletic recruit, URM, Development, the data will not apply to you without such hooks. It was eye opening to see one prep schools private data on who gets in where as it was coded for those things and more. There was not one single unhooked kid who was accepted to Yale from there, out the many who were accepted over time. Not a single one. Princeton and Harvard, a little better, but the numbers were not good at a number of the schools, when the special labels became visible on the blips.
@jennings99 Our school disabled the scattergram for privacy reasons, so the table is all I have to go off of. Do you have any theories for why the avg accepted gpa ED is higher than RD for Brown? I found that kind of odd; maybe it’s an Ivy thing.
@ormdad Thanks for the tip! I’ll try that from now on
@cptofthehouse I’m not sure whether our school measures hooked acceptances, even unofficially. My school is pretty diverse, so I can only hope the acceptances are as well.
