CAT Quant: Score vs Percentile PDF Download

The Quantitative Ability (QA) section is one of the toughest sections of the Common Admission Test (CAT) and often poses a challenge for candidates. This section evaluates a candidate's mathematical abilities, data interpretation skills, and analytical reasoning skills. A high score in this section can significantly improve a candidate's chances of achieving a good percentile score. It is important to understand that the CAT score and percentile score are distinct measures used by business schools in India to assess an applicant's suitability for their MBA program.

CAT Score vs Percentile: Overview

• The CAT score is the total marks obtained by a candidate in the exam. The CAT Exam consists of three sections, including Quantitative Ability, Verbal Ability & Reading Comprehension and Logical Reasoning & Data Interpretation. The marking scheme for the CAT Exam assigns three marks for every correct answer, and there is a negative marking of one mark for every incorrect answer. The final score is the sum of marks obtained in all the sections.

• The CAT percentile score is a relative ranking of a candidate compared to other test-takers. It represents the percentage of candidates who scored lower than the candidate. For example, a 95 percentile score indicates that the candidate scored better than 95% of the total test-takers.

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CAT Quant: Score vs Percentile

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Calculation of Score and Percentile

• To calculate the CAT score, candidates need to count the number of correct and incorrect answers in each section and use the marking scheme to calculate the final score. The sectional scores are added together to arrive at the total score.
• The calculation of percentile score is more complex. The IIMs use a normalization process to adjust the scores across different CAT Exam slots. The process ensures that no candidate is at an advantage or disadvantage due to the difficulty level of a particular slot.

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The CAT percentile score is calculated based on the following formula:

• Percentile score = {(Number of candidates who scored less than the candidate / Total number of candidates)} x 100
• The above formula indicates that the percentile score depends on the total number of test-takers, the number of candidates who scored less than the candidate, and the relative performance of candidates in the slot.

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Frequently Asked Questions (FAQs) on CAT Quant: Score vs Percentile

How is the CAT score calculated in the Quant section?

The CAT score in the Quant section is calculated by counting the number of correct and incorrect answers in the section and using the marking scheme to arrive at the final score. The sectional scores are added together to arrive at the total score.

How is the CAT percentile score calculated in the Quant section?

The CAT percentile score is calculated based on a normalization process used by the IIMs to adjust the scores across different CAT Exam slots. The percentile score is calculated based on the relative performance of candidates in the same slot.

Are the CAT score and percentile directly proportional in the Quant section?

No, the score and percentile are not directly proportional in the Quant section. A high score does not guarantee a high percentile, as the percentile is calculated based on the performance of other candidates in the exam.

What are the factors affecting the CAT percentile in the Quant section?

The factors affecting the CAT percentile in the Quant section include the difficulty level of the exam slot, the number of test-takers in the exam slot, the accuracy level of the candidate's attempts, the percentage of difficult questions attempted by the candidate, and the performance of other candidates in the exam slot.

Is a high CAT percentile score necessary for getting shortlisted for further selection processes in top B-schools?

Yes, a high percentile score is crucial for getting shortlisted for further selection processes in top B-schools. While a high score is necessary, a high percentile score is more important for admission to top B-schools.