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The JEE-Advanced exam was held on 3 October 2021. JEE-Advanced 2022 was scheduled to be held on 3 July 2022 in the usual two sessions - Morning and Afternoon (both compulsory). However, with 2022 JEE-Main being postponed from April/May to 20–29 June/21–30 July, JEE-Advanced 2022 was also postponed and subsequently held on 28 August 2022.
In 2021, 2022, and 2023, it was conducted by IIT Kharagpur, IIT Bombay and IIT Guwahati respectively. The top 250,000 students of JEE Main qualify to appear for the JEE-Advanced examination. In 2018, 224,000 students appeared to take the JEE-Advanced, [9] a number that had gone up from 220,000 in 2017 and 200,000 in 2016. [10]
The number of attempts which a candidate can avail at the examination is limited to three in consecutive years. As of 2018, the top 2,24,000 rankers of JEE-Main will qualify to take the second and final level of examination: JEE-Advanced. this number of 2.24 lakh is not fixed this may vary as per difficulty level of paper of JEE-Main. [7]
In psychometrics, predictive validity is the extent to which a score on a scale or test predicts scores on some criterion measure. [1] [2]For example, the validity of a cognitive test for job performance is the correlation between test scores and, for example, supervisor performance ratings.
A total of 67 students achieved a perfect score, a significantly higher number than in previous examinations, which raised controversy. The National Testing Agency (NTA), the examination organizer, clarified that the higher number of top scorers was due to 44 of the 67 students answering a physics question incorrectly but still being awarded ...
The GATE is used as a requirement for financial assistance (e.g. scholarships) for a number of programs, though criteria differ by admitting institution. [2] In December 2015, the University Grants Commission and MHRD announced that the scholarship for GATE-qualified master's degree students is increased by 56% from ₹ 8,000 (US$92) per month to ₹ 12,400 (US$140) per month.
In statistics, ordinal regression, also called ordinal classification, is a type of regression analysis used for predicting an ordinal variable, i.e. a variable whose value exists on an arbitrary scale where only the relative ordering between different values is significant.
Items that compare equal receive the same ranking number, which is the mean of what they would have under ordinal rankings; equivalently, the ranking number of 1 plus the number of items ranked above it plus half the number of items equal to it. This strategy has the property that the sum of the ranking numbers is the same as under ordinal ranking.