@agrawalmanindra@ni5arga initially after this years' jee adv results i was a little sad that I won't be able to get a decent branch in iit kanpur campus. But after seeing so many of this guy's tweets I think god was protecting me from stupidity.
@shaashvats30@agrawalmanindra exactly? if the data on which chebychev's is applied is itself skewed due to cheating, how will it be effective in pointing out outliers?
I don't think this is Chebyshev's inequality
the latter *upper bounds* the deviation probability in terms of the variance; it's a concentration phenomenon
the phenomenon you're pointing to is the opposite, anti-concentration
it's saying (correctly) that in a random variable with a moderately large variance, we expect to see outliers in a large enough sample
use this upper bound chebychev for Gaokao & between JEE Mains & Advanced (P1 & p2)
Distance of actual from upper bound should be same for all test globally and between JEE Main & JEE advanced
@agrawalmanindra@Travidscot marks in both papers like 70 and 155 are believable...but -3 to 114? you seriously believe it? don't you think its suspiscious?
@agrawalmanindra sir but if we use conditional probability to calculate the marks of these students in 1 paper based on their marks on another paper wouldn't it be very close to 0?
@agrawalmanindra@kvvsgopalrao why are you trying to provide umbrella and shelter to cheaters when students are giving first hand experience of irregularities and cheating happening at their own centers?
@leaveitinthesun@agrawalmanindra sorry cant spend time debating with some one who cant even use 1998 google search tech. 12 students qualled inmo in 2026 from class 12. Anyways work hard, god certainly hasn't given you the brains to make up for that.