How Normalisation Works in CAT:<\/strong><\/p>\n\n\n\n1. Conduct exam in multiple sessions<\/h3>\n\n\n\n
CAT 2025 is held in three slots on November 30, 2025. Each slot has its own question paper designed to be similar in difficulty, but small variations always exist. So the exam authority first treats each session as a separate test for initial scoring.<\/p>\n\n\n\n
2. Calculate raw scores for each candidate<\/h3>\n\n\n\n
For every candidate, raw scores are calculated section-wise and overall using the marking scheme (correct answers, negative marking for wrong answers, and no marks for questions left unattempted). At this stage, scores are not comparable across slots.<\/p>\n\n\n\n
3. Analyse performance pattern in each session<\/h3>\n\n\n\n
The testing body studies how candidates performed in each session: average marks, spread of scores, highest and lowest scores, and distribution of marks. This shows if one slot turned out slightly tougher or easier than another.<\/p>\n\n\n\n
4. Apply a statistical normalisation formula<\/h3>\n\n\n\n
Using statistical methods (similar to standardisation or equating), raw scores in each slot are transformed to a common scale. The idea is that a candidate with the same ability level ends up with a similar scaled score regardless of the slot in which they appeared.<\/p>\n\n\n\n
5. Derive scaled scores for each section and overall<\/h3>\n\n\n\n
After normalisation, each candidate now has scaled scores for VARC, DILR, QA, and for the overall paper. These scaled scores are what appear internally in the CAT system and are used to compute percentiles.<\/p>\n\n\n\n
6. Compute section-wise and overall percentiles<\/h3>\n\n\n\n
For each section and overall, CAT ranks all candidates based on scaled scores and then converts those ranks into percentiles. Your percentile shows the percentage of test-takers who scored less than you. These percentiles finally appear on the CAT 2025 scorecard.<\/p>\n\n\n\n
Example:<\/strong><\/p>\n\n\n\nImagine two candidates:<\/p>\n\n\n\n
\n- Candidate A appears in Slot 1, which turns out slightly tougher.<\/li>\n\n\n\n
- Candidate B appears in Slot 2, which turns out slightly easier.<\/li>\n<\/ul>\n\n\n\n
Suppose both score 60 raw marks in Quant:<\/p>\n\n\n\n
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