I knew a lot of people applied on the last day but I've always been curious about the shape of the curve, so I finally wrote something to track it.
The current rate is about 1.3 applications per minute. I'm guessing that will increase smoothly till the deadline, since the curve looks so smooth so far, but we'll see.
I always wonder what happens with a resubmit (I must have done it tens of times), does the original date still stand? Does it push it to the end of the queue again? Do you see all the revisions?
I've always meant to check if that's a predictor, but anecdotal evidence suggests not. I.e. I know some of the most successful startups applied at the last minute, but not all did.
Is this a graph of the rate of change (acceleration) of applications, or a graph of the raw number of applications submitted? Some labels might be helpful.
Not entirely related, but do you think your assessment of a particular application (team, idea or any other component therein) is influenced at all by the quality of applications that precede and succeed it, especially considering the sheer volume and the rate at which you go through the apps?
Yes, I'm familiar with both, intimately so with the first. I know it occurs, and was wondering to what degree he thinks it does and if there any controls in place.
How is this being updated? The data is encoded in the url, so the link url must be changing periodically. Doesn't this mean 'nthnclrk' is doing the charting?
Would like to see this curve if it was a real-time updating chart publicly available on HN :P
(P.S Don't forget the username when reading my application!)
An interesting (albeit impossible to track) metric would be how much time the average YC application took - and if the time spent correlates with acceptance at all.
I wonder if that graph would look closer to a bell curve or exponential decay.
An increase in time spent would not increase the success rate. Probably the opposite. More time spent -- less likely that an applicant is on the right track.
Applicants that submit at the last minute have likely been thinking about/living with the problem for a while, and they are able to quickly articulate the problem, their solution, and the reason that they will be successful.
We agree. Both the bell curve and the exponential delay curve would mean the more time spent on the application, the less likely that team is to be accepted.
TL;DR: I may or may not have contributed to a point on that curve and I am not sure how to feel about it.
I began filling out the form on the day the application window was announced. Halfway through, I realized the answers I had to some of the questions on the form, were either unconvincing or simply non-existent. As I progressed, I realized that me and my idea both sounded increasingly half-assed, so I promptly stopped, saved the form, quietly went back to the drawing board and started attempting to figure out the answers.
It has been roughly two months since that day, I guess. I still don't have all the answers but I can at least tell myself now that the idea is worth a shot...
Curious if you've speculated about the reason for the high volume of late applications, especially since you're pretty clear that early apps have a better chance to get accepted.
Any guess on correlation between location of applicant and proximity of application time to deadline? Is the 8pm PST deadline keeping the European applicants up late?
It would be interesting to know more about the (historical) distribution of the overall applications, especially how many are settled within the last one percent quantile of time.
Assuming a distribution and working with a simple e-function, around 3.500 total applications with an acceptance rate around 1.25% (batch<50) might be a ballpark estimate.
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[ 3.3 ms ] story [ 112 ms ] threadThe current rate is about 1.3 applications per minute. I'm guessing that will increase smoothly till the deadline, since the curve looks so smooth so far, but we'll see.
And yes, I think the rate will probably continue to accelerate till the deadline.
I ended up on:
http://mathworld.wolfram.com/SultansDowryProblem.html
I only picked up the URL via his twitter post.
I wonder if that graph would look closer to a bell curve or exponential decay.
Applicants that submit at the last minute have likely been thinking about/living with the problem for a while, and they are able to quickly articulate the problem, their solution, and the reason that they will be successful.
I began filling out the form on the day the application window was announced. Halfway through, I realized the answers I had to some of the questions on the form, were either unconvincing or simply non-existent. As I progressed, I realized that me and my idea both sounded increasingly half-assed, so I promptly stopped, saved the form, quietly went back to the drawing board and started attempting to figure out the answers.
It has been roughly two months since that day, I guess. I still don't have all the answers but I can at least tell myself now that the idea is worth a shot...
May it be one of the first of many such convex curves.
Reminds me of Nasim Taleb's smile and frown demonstrations vis a vis fragility and anti-fragility.
Assuming a distribution and working with a simple e-function, around 3.500 total applications with an acceptance rate around 1.25% (batch<50) might be a ballpark estimate.