Anonymous wrote:You can only do this math if the events are independent, which is obviously not the case.Anonymous wrote:Look, forecasters don't get the future inflation number or the USD-JPY rate correctly most of the time, but it doesn't stop them from using reason to arrive at a forecast , and they get the direction right most of the time even if not the exact number.
OP is similarly using reason. And the math is correct if you assume a set of qualified students whose stats put them in the range of these schools.
OP used 4% acceptance as an example. You can use Naviance to actually get a sense of probability of not being accepted to a school for your stats (calculate acceptance for that higher stat cluster). So let's say using the Naviance plot of GPA and SAT, your child has a 15% probability of admit at Cornell, and a 15% admit at Dartmouth, (that would be 85% probability of rejection at each). So the probability of rejection FROM BOTH is
0.85*0.85= 0.7225 , i.e. 72%.
If Harvard is a 8% admit probability for your stats, then the probability of reject from ALL THREE is
0.92*0.85*0.85= 0.6647 (66%).
The math is correct...and the correct interpretation is:
1. For those students whose stats put them within the range, applying to more elite schools lowers the likelihood of being rejected by all or put another way improves the probability of being accepted by at least one.
2. But that said , the resultant rejection probability is still high and for most of the best kids rarely gets better than a coin toss.
You don't get shattered when you lose a coin toss. Don't get shattered when your kid doesn't get into an elite.
Anonymous wrote:The occurrence of one does affect the probability of the others also occurring. If a student is in at MIT and Harvard, there is a greater than 4% chance of them also being in at Princeton.Anonymous wrote:Anonymous wrote:They are not totally independent, but also not totally dependent. But your point is taken.
The takeaway is that college admission is NOT a lottery system like some posters claimed.
If your stats puts on in the game, you want to apply to AS MANY top 20 as possible!!!
In mathematical terms, related to game theory, they are totally independent events, in that the outcome of one does not affect the outcome of another.
https://mathematicalmysteries.org/independent-and-dependent-events/
But as noted, despite that you cannot use game theory because you can’t know the starting odds of your admission the way you can know that you have a 1 in 52 chance of drawing the 8 of hearts from a full deck of cards.
Anonymous wrote:You can only do this math if the events are independent, which is obviously not the case.Anonymous wrote:Look, forecasters don't get the future inflation number or the USD-JPY rate correctly most of the time, but it doesn't stop them from using reason to arrive at a forecast , and they get the direction right most of the time even if not the exact number.
OP is similarly using reason. And the math is correct if you assume a set of qualified students whose stats put them in the range of these schools.
OP used 4% acceptance as an example. You can use Naviance to actually get a sense of probability of not being accepted to a school for your stats (calculate acceptance for that higher stat cluster). So let's say using the Naviance plot of GPA and SAT, your child has a 15% probability of admit at Cornell, and a 15% admit at Dartmouth, (that would be 85% probability of rejection at each). So the probability of rejection FROM BOTH is
0.85*0.85= 0.7225 , i.e. 72%.
If Harvard is a 8% admit probability for your stats, then the probability of reject from ALL THREE is
0.92*0.85*0.85= 0.6647 (66%).
The math is correct...and the correct interpretation is:
1. For those students whose stats put them within the range, applying to more elite schools lowers the likelihood of being rejected by all or put another way improves the probability of being accepted by at least one.
2. But that said , the resultant rejection probability is still high and for most of the best kids rarely gets better than a coin toss.
You don't get shattered when you lose a coin toss. Don't get shattered when your kid doesn't get into an elite.
You can only do this math if the events are independent, which is obviously not the case.Anonymous wrote:Look, forecasters don't get the future inflation number or the USD-JPY rate correctly most of the time, but it doesn't stop them from using reason to arrive at a forecast , and they get the direction right most of the time even if not the exact number.
OP is similarly using reason. And the math is correct if you assume a set of qualified students whose stats put them in the range of these schools.
OP used 4% acceptance as an example. You can use Naviance to actually get a sense of probability of not being accepted to a school for your stats (calculate acceptance for that higher stat cluster). So let's say using the Naviance plot of GPA and SAT, your child has a 15% probability of admit at Cornell, and a 15% admit at Dartmouth, (that would be 85% probability of rejection at each). So the probability of rejection FROM BOTH is
0.85*0.85= 0.7225 , i.e. 72%.
If Harvard is a 8% admit probability for your stats, then the probability of reject from ALL THREE is
0.92*0.85*0.85= 0.6647 (66%).
The math is correct...and the correct interpretation is:
1. For those students whose stats put them within the range, applying to more elite schools lowers the likelihood of being rejected by all or put another way improves the probability of being accepted by at least one.
2. But that said , the resultant rejection probability is still high and for most of the best kids rarely gets better than a coin toss.
You don't get shattered when you lose a coin toss. Don't get shattered when your kid doesn't get into an elite.
The occurrence of one does affect the probability of the others also occurring. If a student is in at MIT and Harvard, there is a greater than 4% chance of them also being in at Princeton.Anonymous wrote:Anonymous wrote:They are not totally independent, but also not totally dependent. But your point is taken.
The takeaway is that college admission is NOT a lottery system like some posters claimed.
If your stats puts on in the game, you want to apply to AS MANY top 20 as possible!!!
In mathematical terms, related to game theory, they are totally independent events, in that the outcome of one does not affect the outcome of another.
https://mathematicalmysteries.org/independent-and-dependent-events/
But as noted, despite that you cannot use game theory because you can’t know the starting odds of your admission the way you can know that you have a 1 in 52 chance of drawing the 8 of hearts from a full deck of cards.
All the mentioned colleges are mostly looking for the same students -- highly accomplished with impressive ECs and an interesting story.Anonymous wrote:Anonymous wrote:Anonymous wrote:Except that's not how it works, because each of those independent events is dependent on mostly the same factors.
This can't be true. JHU and Cornell are looking for different students, so are MIT and Yale.
Your reasoning reduces college admission to simple stats such as test score and gpa. However, that is not how it works!
OP's reasoning is falling into that trap, not this PP. Negative correlation is not zero correlation.
If Yale doesn't like what MIT likes, the student who might get into MIT, will gain almost nothing applying to Yale.
If Yale and Cornell like nearly the same thing, the student who applies to both is likely to get the same result from both applications.
Then they're not independentAnonymous wrote:Except that's not how it works, because each of those independent events is dependent on mostly the same factors.
Anonymous wrote:Anonymous wrote:
You can’t do the math without knowing the factors, and you have no idea what the factors are for an individual applicant.
Weather forecasts don’t wait to measure every gust of wind to predict rain—they model with temperature and pressure alone. Admission odds can be modeled with GPA and SAT, even if extracurriculars and essays aren’t known.
Anonymous wrote:
You can’t do the math without knowing the factors, and you have no idea what the factors are for an individual applicant.
Anonymous wrote:Anonymous wrote:
WRT an individual applicant, whose likelihood could be 0% or 100% at any one college.
There is a 100% likelihood of an applicant being between 0% to 100%, so that is quite a meaningless understanding of probability.
Probability is about trying to quantify uncertainty. The more complete the model, the lower the error range/standard deviation. So sure, if someone had a line of sight on acceptances based on SAT+GPA+ ECs they would have a better model than someone with just a line of sight on SAT+GPA.
But the only public data that can be modelled comes from Naviance (school level SAT+GPA) and CDS (overall acceptances accurate, SAT+GPA based on those reporting). For those who are so inclined, they can calculate their probabilities of rejection from each and multiply them.
I think the third interpretation from the math for me is very clear, if applying to reaches, apply to a whole bunch of them , it will improve your chances of acceptance to at least one. Applying only to say Harvard is quite meaningless.
Anonymous wrote:
WRT an individual applicant, whose likelihood could be 0% or 100% at any one college.
Anonymous wrote:Anonymous wrote:Look, forecasters don't get the future inflation number or the USD-JPY rate correctly most of the time, but it doesn't stop them from using reason to arrive at a forecast , and they get the direction right most of the time even if not the exact number.
OP is similarly using reason. And the math is correct if you assume a set of qualified students whose stats put them in the range of these schools.
OP used 4% acceptance as an example. You can use Naviance to actually get a sense of probability of not being accepted to a school for your stats (calculate acceptance for that higher stat cluster). So let's say using the Naviance plot of GPA and SAT, your child has a 15% probability of admit at Cornell, and a 15% admit at Dartmouth, (that would be 85% probability of rejection at each). So the probability of rejection FROM BOTH is
0.85*0.85= 0.7225 , i.e. 72%.
If Harvard is a 8% admit probability for your stats, then the probability of reject from ALL THREE is
0.92*0.85*0.85= 0.6647 (66%).
The math is correct...and the correct interpretation is:
1. For those students whose stats put them within the range, applying to more elite schools lowers the likelihood of being rejected by all or put another way improves the probability of being accepted by at least one.
2. But that said , the resultant rejection probability is still high and for most of the best kids rarely gets better than a coin toss.
You don't get shattered when you lose a coin toss. Don't get shattered when your kid doesn't get into an elite.
WRT an individual applicant, whose likelihood could be 0% or 100% at any one college.
Anonymous wrote:Look, forecasters don't get the future inflation number or the USD-JPY rate correctly most of the time, but it doesn't stop them from using reason to arrive at a forecast , and they get the direction right most of the time even if not the exact number.
OP is similarly using reason. And the math is correct if you assume a set of qualified students whose stats put them in the range of these schools.
OP used 4% acceptance as an example. You can use Naviance to actually get a sense of probability of not being accepted to a school for your stats (calculate acceptance for that higher stat cluster). So let's say using the Naviance plot of GPA and SAT, your child has a 15% probability of admit at Cornell, and a 15% admit at Dartmouth, (that would be 85% probability of rejection at each). So the probability of rejection FROM BOTH is
0.85*0.85= 0.7225 , i.e. 72%.
If Harvard is a 8% admit probability for your stats, then the probability of reject from ALL THREE is
0.92*0.85*0.85= 0.6647 (66%).
The math is correct...and the correct interpretation is:
1. For those students whose stats put them within the range, applying to more elite schools lowers the likelihood of being rejected by all or put another way improves the probability of being accepted by at least one.
2. But that said , the resultant rejection probability is still high and for most of the best kids rarely gets better than a coin toss.
You don't get shattered when you lose a coin toss. Don't get shattered when your kid doesn't get into an elite.
Anonymous wrote:Assuming they are all independent separate events, the probability of receiving at least one acceptance is 33% if you apply to 10 colleges each with 4% admit rate.