How to Prepare for DATA INTERPRETATION for CAT Paperback Arun Sharma (Author) Tata McGrawHill

680

The 8th edition of How to Prepare for Data Interpretation for CAT has been developed as per the latest trend and pattern of the CAT examination. This book is a one-stop solution for CAT and MBA examinations aspirants to excel in the Data Interpretation section of all key management entrance examinations. It also contains the best advisory for each and every type of questions asked in the competitive examinations.With this book, you get access to McGraw Hill Edge – a digital platform with high-quality learning resources that provides you the edge to excel at your exams.

On the McGraw Hill Edge platform, you can access mock test, practice tests, expert sessions, comprehensive study materials and exam preparation strategies, all designed to enhance your preparation and give you the winning edge. Moreover, its mobile and web app interface makes learning convenient and accessible! Follow the instructions given in the book to get access.

Salient Features of the book:

1. Comprehensive coverage of Data Interpretation in three Sections – Traditional Data Interpretation, Logical Data Interpretation and Solved CAT Papers (2021 and 2022)

2. Traditional Data Interpretation provides exhaustive view and study resources including –

a. Basic Modes of Data Interpretation

b. How to think in Data Interpretation

c. 26 Mock Test Papers (Split in levels of difficulty 1 and 2)

3. Logical Data Interpretation comprehensively follows latest CAT pattern including –

a. How to think in Logical Data Interpretation

b. 30 Twelve-Minute Test Papers

c. 28 Mock Test Papers (Split in levels of difficulty 2 and 3)

4. Solved CAT Papers containing in-depth analysis and solutions

5. Detailed solutions to questions in all levels of difficulties (LODs)

6. Exhaustive and time-bound practice questions to strengthen speed-with-accuracy

7. Access to solved Previous Year CAT Papers (2020-2022), 2 Mock Tests and 3 Sectional Tests on McGraw Hill Edge

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