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YUGROWINTo rank candidates in all of our scholarship tests, we use a measure called yu Score. This score is based on the marks obtained and time taken by the candidate for a given test. This blog post explains the definiton of this score along with how it is used to rank the candidates.
yu score of any candidate is based on the marks score and time taken by the candidate for a given test. This score will always lie between 0 to 1 and we calculate this score till the 6th decimal place to ensure ranking is transparent and avoid collision/tie of ranks. It is calculated as follows
Where:
Candidate | Total Marks | Total Time Allowed | Marks Scored | Time taken | Pt | Pm | yuScore |
Candidate 1 | 200 | 3600000 ms | 189 | 3598450 ms | 0.945000 | 0.999569 | 0.756086 |
Candidate 2 | 200 | 3600000 ms | 143 | 3513216 ms | 0.715000 | 0.975893 | 0.576821 |
We rank all candidates based on thier yu score and then apply relevant cutoffs to decide who wins the scholarship grant if any. Here is an example.
Lets say the test with the below specifications and offers the following grants against the defined yu score cutoffs.
Grant Amount | Count of Scholarships | yu score Cutoff |
₹ 500,000 | 2 | 0.760001 and above |
₹ 300,000 | 4 | 0.720001 and above |
₹ 100,000 | 6 | 0.680001 and above |
Here is the sample performance table of the 25 candidates who attended this test. Please scroll right to view the whole table.
Candidate | Total Questions | Total Marks | Time Allowed | Questions Attempted | Questions Unattempted | Correct Answers | InCorrect Answers | Marks Obtained | Time Taken | Pm | Pt | yu Score |
Candidate 1 | 50 | 100 | 3600000 | 50 | 0 | 49 | 1 | 96.50 | 2927439 | 0.965000 | 0.813178 | 0.809365 |
Candidate 2 | 50 | 100 | 3600000 | 49 | 1 | 48 | 1 | 94.00 | 3203423 | 0.940000 | 0.889840 | 0.774032 |
Candidate 3 | 50 | 100 | 3600000 | 47 | 3 | 46 | 1 | 89.00 | 3106454 | 0.890000 | 0.862904 | 0.739419 |
Candidate 4 | 50 | 100 | 3600000 | 48 | 2 | 48 | 0 | 95.00 | 3073988 | 0.950000 | 0.853886 | 0.789223 |
Candidate 5 | 50 | 100 | 3600000 | 50 | 0 | 37 | 13 | 54.50 | 2985011 | 0.545000 | 0.829170 | 0.470166 |
Candidate 6 | 50 | 100 | 3600000 | 47 | 3 | 47 | 0 | 92.50 | 3424499 | 0.925000 | 0.951250 | 0.749750 |
Candidate 7 | 50 | 100 | 3600000 | 48 | 2 | 38 | 10 | 60.00 | 3379461 | 0.600000 | 0.938739 | 0.492252 |
Candidate 8 | 50 | 100 | 3600000 | 49 | 1 | 45 | 4 | 83.50 | 3399867 | 0.835000 | 0.944408 | 0.679119 |
Candidate 9 | 50 | 100 | 3600000 | 48 | 2 | 45 | 3 | 84.50 | 3258594 | 0.845000 | 0.905165 | 0.694967 |
Candidate 10 | 50 | 100 | 3600000 | 50 | 0 | 37 | 13 | 54.50 | 3216239 | 0.545000 | 0.893400 | 0.457320 |
Candidate 11 | 50 | 100 | 3600000 | 50 | 0 | 44 | 6 | 79.00 | 3362719 | 0.790000 | 0.934089 | 0.645182 |
Candidate 12 | 50 | 100 | 3600000 | 46 | 4 | 40 | 6 | 69.00 | 3352336 | 0.690000 | 0.931204 | 0.565759 |
Candidate 13 | 50 | 100 | 3600000 | 50 | 0 | 37 | 13 | 54.50 | 2945212 | 0.545000 | 0.818114 | 0.472377 |
Candidate 14 | 50 | 100 | 3600000 | 49 | 1 | 35 | 14 | 48.50 | 2957078 | 0.485000 | 0.821411 | 0.423718 |
Candidate 15 | 50 | 100 | 3600000 | 48 | 2 | 48 | 0 | 95.00 | 2883636 | 0.950000 | 0.801010 | 0.799798 |
Candidate 16 | 50 | 100 | 3600000 | 50 | 0 | 39 | 11 | 61.50 | 3181140 | 0.615000 | 0.883650 | 0.515270 |
Candidate 17 | 50 | 100 | 3600000 | 46 | 4 | 44 | 2 | 83.00 | 3079889 | 0.830000 | 0.855525 | 0.692895 |
Candidate 18 | 50 | 100 | 3600000 | 48 | 2 | 45 | 3 | 84.50 | 3496832 | 0.845000 | 0.971342 | 0.681732 |
Candidate 19 | 50 | 100 | 3600000 | 48 | 2 | 48 | 0 | 95.00 | 3209114 | 0.950000 | 0.891421 | 0.781716 |
Candidate 20 | 50 | 100 | 3600000 | 50 | 0 | 48 | 2 | 93.00 | 3122776 | 0.930000 | 0.867438 | 0.770512 |
Candidate 21 | 50 | 100 | 3600000 | 47 | 3 | 38 | 9 | 61.00 | 3195067 | 0.610000 | 0.887519 | 0.510496 |
Candidate 22 | 50 | 100 | 3600000 | 48 | 2 | 42 | 6 | 74.00 | 3393045 | 0.740000 | 0.942513 | 0.603498 |
Candidate 23 | 50 | 100 | 3600000 | 50 | 0 | 37 | 13 | 54.50 | 3376528 | 0.545000 | 0.937924 | 0.448415 |
Candidate 24 | 50 | 100 | 3600000 | 48 | 2 | 42 | 6 | 74.00 | 3205194 | 0.740000 | 0.890332 | 0.613934 |
Candidate 25 | 50 | 100 | 3600000 | 47 | 3 | 42 | 5 | 75.00 | 3569236 | 0.750000 | 0.991454 | 0.601709 |
Based on the above results we assign rank to each candidate based on the yu score and put the candidates on an ascending order of the rank. After this, we apply the qualifying cutoffs for relevant grant schedule to define who gets which grant.
It is important to note that
Candidate | Pm | Pt | yu Score | Rank | Grant 1 | Grant 2 | Grant 3 | Scholarship |
Candidate 1 | 0.965000 | 0.813178 | 0.809365 | 1 | Qualifies CutOff | Qualifies CutOff | Qualifies CutOff | 500000 |
Candidate 15 | 0.950000 | 0.801010 | 0.799798 | 2 | Qualifies CutOff | Qualifies CutOff | Qualifies CutOff | 500000 |
Candidate 4 | 0.950000 | 0.853886 | 0.789223 | 3 | Qualifies CutOff | Qualifies CutOff | Qualifies CutOff | 300000 |
Candidate 19 | 0.950000 | 0.891421 | 0.781716 | 4 | Qualifies CutOff | Qualifies CutOff | Qualifies CutOff | 300000 |
Candidate 2 | 0.940000 | 0.889840 | 0.774032 | 5 | Qualifies CutOff | Qualifies CutOff | Qualifies CutOff | 300000 |
Candidate 20 | 0.930000 | 0.867438 | 0.770512 | 6 | Qualifies CutOff | Qualifies CutOff | Qualifies CutOff | 300000 |
Candidate 6 | 0.925000 | 0.951250 | 0.749750 | 7 | Does not Qualify | Qualifies CutOff | Qualifies CutOff | 100000 |
Candidate 3 | 0.890000 | 0.862904 | 0.739419 | 8 | Does not Qualify | Qualifies CutOff | Qualifies CutOff | 100000 |
Candidate 9 | 0.845000 | 0.905165 | 0.694967 | 9 | Does not Qualify | Does not Qualify | Qualifies CutOff | 100000 |
Candidate 17 | 0.830000 | 0.855525 | 0.692895 | 10 | Does not Qualify | Does not Qualify | Qualifies CutOff | 100000 |
Candidate 18 | 0.845000 | 0.971342 | 0.681732 | 11 | Does not Qualify | Does not Qualify | Qualifies CutOff | 100000 |
Candidate 8 | 0.835000 | 0.944408 | 0.679119 | 12 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |
Candidate 11 | 0.790000 | 0.934089 | 0.645182 | 13 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |
Candidate 24 | 0.740000 | 0.890332 | 0.613934 | 14 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |
Candidate 22 | 0.740000 | 0.942513 | 0.603498 | 15 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |
Candidate 25 | 0.750000 | 0.991454 | 0.601709 | 16 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |
Candidate 12 | 0.690000 | 0.931204 | 0.565759 | 17 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |
Candidate 16 | 0.615000 | 0.883650 | 0.515270 | 18 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |
Candidate 21 | 0.610000 | 0.887519 | 0.510496 | 19 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |
Candidate 7 | 0.600000 | 0.938739 | 0.492252 | 20 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |
Candidate 13 | 0.545000 | 0.818114 | 0.472377 | 21 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |
Candidate 5 | 0.545000 | 0.829170 | 0.470166 | 22 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |
Candidate 10 | 0.545000 | 0.893400 | 0.457320 | 23 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |
Candidate 23 | 0.545000 | 0.937924 | 0.448415 | 24 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |
Candidate 14 | 0.485000 | 0.821411 | 0.423718 | 25 | Does not Qualify | Does not Qualify | Does not Qualify | 0 |