CAT Normalization Process. Know How is CAT Score Calculated, CAT Percentile Predictor

Ridhima Jindal

Updated on 28th November, 2024 , 4 min read

The CAT exam was recently conducted on 24th November 2024, on a Sunday. The exam was conducted as an online computer-based-test (CBT). Now the candidates are eagerly waiting for the CAT Results 2024 and are eager to know the colleges they can apply to. In this news, we will help the candidates understand the meaning of CAT normalization process, CAT Scaled Score, CAT Final Score, and how to calculate the CAT scores.

What is the CAT Normalization Process?

CAT Normalization is a process that is followed by the Indian Institutes of Management to ensure fairness in the scoring process. Since the CAT Exam is conducted in multiple slots and the question paper for each slot is different in terms of both questions and difficulty, some students get an easier paper while some get a tough one. 

In simple terms, it is the process of adjusting scores to the same level for all the applicants and takes into consideration, various factors like the difficulty level of the exam, individual candidate abilities, and variations in the number of questions attempted. These scaled scores are then converted into CAT percentiles, based on which the candidates are selected or shortlisted for further CAT admission rounds at IIMs.

CAT Percentile Predictor

With the excitement continuing for the CAT results 2024, candidates are also eager to know what their percentile can be and what can they expect as per their attempts. Candidates can use our “CAT Percentile Predictor” tool to predict their expected percentile and scores.

CAT Percentile Predictor

CAT Normalisation Process

The CAT normalization process will typically involve two steps - Calculation of Raw scores and then normalization of CAT raw scores. Each of these steps has been explained in detail below.

You can also read: What after the CAT Result?

Calculation of CAT Raw Scores

CAT raw score is nothing, but the actual and raw score that the candidates think they will get. To determine the CAT Raw scores, the candidates first should be aware of the three basic things listed below. To know their raw scores, candidates will utilize the CAT answer key (final).

1. CAT Marking Scheme (+3, -1)

2. Number of Correct Answers

3. Number of Incorrect Answers

Formula to Calculate Raw  Scores

Once the above printers have been taken into consideration and the candidates have gathered the information, the following formula will be used to determine the CAT score.

Raw Score = 3 x (No. of Correct Answers) - 1 x (No. of Incorrect Answers)

For example: Let us assume that a candidate has 33 correct answers and 33 incorrect answers. So using the formula given above, the raw score of the candidate will be:

3 x (33) - 1 x (33) = 99 - 33 = 66 out of 198

Now, once the raw scores have been determined, the normalization procedure may be used to obtain the candidate's CAT-scaled score. The scaled scores of a candidate are included in the CAT scorecard that is made public following the announcement of CAT Results. The CAT scaled scores are also used to compute the percentile for the CAT, whether it be overall or section-wise.

It is preferable to break the procedure down into many phases and comprehend each variable that is utilized in the calculation in order to more readily comprehend the normalization of CAT scores. 

Calculation of CAT Scaled Score / CAT Normalization

Let us now start by understanding the processes for calculating the CAT scaled score. These procedures are used section-by-section, meaning that while computing scaled scores, only one section's raw values are taken into account at a time. This typically means that the scaled scores will be calculated for each section, and each slot individually.

Steps to Calculate the CAT Scaled Score

Step 1: The mean (Average) and standard deviation (SD) of the candidates' raw scores from the first shift are calculated and added.

M1 = Mean of 1st Shift + SD of 1st Shift

Step 2: For applicants who appeared in the second shift, the mean and standard deviation of their raw scores are calculated and added.

M 2 = Mean of 2nd Shift + SD of 1st Shift

Step 3: For applicants who appeared in the third shift, the mean and standard deviation of their raw scores are calculated and added.

M 3 = Mean of 3rd Shift + SD of 1st Shift

Step 4: For applicants who appeared in all three shifts, the mean and standard deviation of their raw scores are calculated and added.

M = Mean of all the three Shifts + SD of all the three Shifts

Step 5: The top 0.1% of applicants who appeared in the first shift have their raw scores averaged out.

Let this be M1.01

Step 6:  The top 0.1% of applicants who appeared in the second shift have their raw scores averaged out.

Let this be M2.01

Step 7: The top 0.1% of applicants who appeared in the third shift have their raw scores averaged out.

Let this be M3.01

Step 8: The top 0.1% of applicants who appeared in the both sections have their raw scores averaged out.

Let this be M0.1

Step 9: The scaled score of a candidate is calculated using the formula below. Please keep in mind that the calculation provided is for a candidate who appeared for the first shift.

Scaled Score = M + {(R - M1) x (M0.1 - M) / (M1.01 - M1)}

To determine a candidate's scaled score for the other two shifts, the relevant variables in this formula must be adjusted appropriately. Here, R stands for the candidate's raw score, from which the scaled score is being derived.

Overall Scaled Score = Scaled Score in DILR + Scaled Score in QA + Scaled Score in VARC

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