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Normalization of Scores in CAT 2016

Last Updated - November 25, 2016

The CAT 2016 Exam is set to be conducted on Dec 04, 2016. The Exam will be conducted in two sessions on Dec 04, 2016. IIM Bangalore will use normalization of scores across for these two sessions of CAT 2016. The Normalization of CAT 2016 Scores is implemented to adjust for location and different sessions. The score distributions across different forms and the scaled scores obtained by this process shall be converted into percentiles for purposes of shortlisting.

Before you start, please note that the exact formula that the IIMs may use for normalizing the CAT 2016 scores is not yet known, and any formula that is mentioned within this article is given solely for the purpose of illustrating the fundamental concepts of normalization and the process that is likely to be used by the IIMs.

Normalization of CAT 2016 Scores

The CAT official website elaborates CAT Normalization as, “CAT 2016 will be conducted in two sessions. In two sessions, two different test forms will be administered. Across different test sessions, the scores of the candidates will be subjected to a process of Normalization.”

Across all the sessions of CAT Exam, the distribution of scores can be expected to differ in terms of the exact values of the two characteristic parameters, i.e., the mean (location), µ”, and the standard deviation (scale), σ”. The differences could be slight or significant, depending on how close the question papers are in terms of their difficulty level and on how similar the test taking groups are across the four sessions.

However, these differences in mean and standard deviation (also referred to as differences in location and scale) can be resolved by using different mathematical approaches. The final Result of CAT Exam is released after normalization of scores.

Method of Normalization

The Normalization is a type of percentile equivalence method. For reporting purposes, Scaled scores for each section (Section I: Verbal Ability and Reading Comprehension (VARC), Section II: Data Interpretation and Logical Reasoning (DILR), and Section III: Quantitative Ability (QA)) and Final Scores along with the Percentile scores are published.

Normalization of CAT 2016 Scores

M= Normalised Marks

s = Marks obtained by the candidate in section/total

µ = Average Mean

σ = standard deviation

Now, as an example, consider that the mean score of all the CAT 2016 test takers in Section-I in Session 1 is 42 marks and the standard deviation is 26 marks, and the actual score obtained by a student A (who appeared in Session 1) in Section-I is 76. Then, the normalized score of student A in Section-I will be (76 – 42)/26 ≅ 1.4166

Similarly, Let’s say the mean score in Section-I of all the CAT 2016 test takers in Session 2 is 39 marks and the standard deviation, 24 marks. Let the actual score obtained by a student B in Section-I be 84 (for comparison purposes, same as that for student A). Then, the normalized score of student B in Section-I will be (84 – 39)/24 ≅ 1.875

The normalized scores of CAT thus obtained for all the students across all sessions (in a particular section or the total) will then be used to calculate the sectional and overall percentiles.

In the above case, since the normalized scores are fractional and cannot be compared easily, the normalized scores could possibly be multiplied with a constant in order to arrive at integer scores, only for reporting purposes. For example, if the constant is chosen as 50, then the final scaled scores, of students A and B, that will be reported are 71 (i.e., 1.4166 * 50 ≅ 70.83, rounded off to 71) and 94 (i.e., 1.875 * 50 ≅ 93.75, rounded off to 94) respectively.



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