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LRDI- Set 6 Video Lecture | Crash Course for CAT

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FAQs on LRDI- Set 6 Video Lecture - Crash Course for CAT

1. What is LRDI in CAT?
Ans. LRDI stands for Logical Reasoning and Data Interpretation, which is a section in the Common Admission Test (CAT) exam. It assesses a candidate's ability to analyze and interpret complex data sets, make logical deductions, and solve problems based on logical reasoning.
2. How is the LRDI section structured in the CAT exam?
Ans. The LRDI section in the CAT exam consists of sets of questions based on data interpretation and logical reasoning. Candidates are required to analyze given data sets, make calculations, draw conclusions, and solve problems based on logical reasoning within a time limit. The section usually includes multiple-choice questions and requires a strategic approach to maximize score.
3. What type of questions can be expected in the LRDI section of CAT?
Ans. The LRDI section of CAT can include various types of questions such as data interpretation tables, charts, graphs, and puzzles. Candidates may be asked to analyze data, find patterns, solve logical puzzles, make deductions, and evaluate arguments. The questions may vary in difficulty level and require strong analytical and logical thinking skills.
4. How can I improve my performance in the LRDI section of CAT?
Ans. To improve performance in the LRDI section of CAT, you can practice solving a variety of data interpretation and logical reasoning questions. Focus on developing your analytical and logical thinking abilities. Try to solve different types of puzzles, practice speed calculation, and enhance your data interpretation skills. Mock tests and previous year question papers can also help in gaining familiarity with the exam pattern and managing time effectively.
5. Are there any specific strategies to approach the LRDI section in CAT?
Ans. Yes, there are specific strategies that can be employed while approaching the LRDI section in CAT. It is important to carefully read the question and understand the given data. Identify the key information and try to simplify complex data sets. Prioritize questions based on difficulty level and time required. Use logical reasoning techniques to solve problems efficiently. It is also advisable to practice time management and avoid spending too much time on a single question.
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