riverripper wrote:
I am not sure how much help it would be with the ultra elites since it seems a lot of that is random or based heavily on essays.
Here is what I would find the most useful....though it might be too much to do specific schools but it might be great to have one that you enter the information you stated. GMAT, GPA, Age, Years experiences, rank leadership, and extra curriculars. Then your desired field post graduation. Then give a list of 5 schools that meet their goals ranging from a reach school whether its H/S/W or a school in the top 20s...all the way to a safety school for them. Eventually it would be great if you could include factors like desired location, whether work experience is name brand, quality of undergrad, and even where the person is from (we have all heard rumors of certain schools being very hard for Indians to get into).
Probably far to much to ask for unless someone around here is a software engineer with way too much freetime and access to lots of stats for tons and tons of schools...might want to limit it to top 50s or something haha.
Very helpful info. thank you
GMATcram wrote:
I've seen that nationality plays imporant role on admit. Female is also an advantage when applying to MBA program.
Indeed. Thank you for this.
aaudetat wrote:
I'm the last person to ask about probabilities and the like. I barely know what regression is. It seems that the intangibles are SO important; how can we predict? I think of the butterfly in Australia causing the tornado in Iowa -- so many variables between Sydney and Cedar Rapids: how can you ever imagine how each will play off the next? I leave it to you all, of course, but coming from a customer service standpoint, I would hate for applicants to over-apply or under-apply based on an unproven estimator.
I think a more basic "basic stats comparison" tool would be an easy place to start. During my search, I made a table of about 10 schools and color-coded it to show how I compared to the school's averages: green for above average (ie my 710 GMAT compared to School X's 680 average), yellow for average, and red for below average. Then I assigned each school a rating of stretch, possible, and likely.
As for the intangibles, I made my own judgement on the relative value of my essays, experiences, interview skills, etc.
aaudetat
Good points. Your concern about members using the estimator to make such critical decisions is justified.
The estimator will have user input by current admitted students. All admitted students can input data and rank the intangibles on a scale of 1 to 10. So, we are making recommendations based on data. By no means are we saying that this can replace common sense.
I had a horrible teacher for Sarcasm 101 in undergrad, so forgive me if you were joking about Regression and Probabilities. What we try to do is to look at say, Admit to Duke (Variable Y, the "response" variable) and input known explanatory variables such as age (X1), GPA(X2) , ...Extra curriculars (Xn). We have data on the explanatory variables. So we can run a regression for each such school based on the data we have.
About probabilities, simply compare the total number of students with a user specified profile who applied to Duke (The user can specify a range of AGE, GPA etc). Then go look for similar profiles in the database and determine how many such students were accepted. Divide (acceptances) / (total number of such profiles) gives you the probability.
We will also look up recommendations made by Paul Bodine, Linda, MBA Game Plan and try to compare them with our own estimator. This will serve to validate our results.
thanks
Hjort wrote:
Neat idea- I am happy to help out.
A few additional factors:
1. Perceived Quality of Undergrad Institution/Major
2. Graduate School
I find the EASDL "Risks" framework a useful model to have in mind but there are clearly other ways to view admissions.
https://www.gmatclub.com/phpbb/viewtopic.php?t=19450You are insightful as always. Two more factors to the list . Thanks.
This is getting interesting.
lepium wrote:
I think this estimation will be much more fallible than the one to estimate GMAT scores.
I seem to be the quite alone (based on the stats obsession all around us), but I buy into the holistic nature of the application, so I don't think the predictor would be of any help other than to give some ballpark odds (probably aligned with Hjort's cluster system).
Anyway, it's always better to have some indication than nothing at all.
Cheers. L.
Agreed. We want to emphasize the "estimator" part. It is not intended to replace common sense.