CAT (Common Admission Test) Data Interpretation (DILR) Flashcards

24 sample cards from the Data Interpretation (DILR) deck

Sampled from the end of the deck, so these are different cards from the ones shown on the syllabus page.

1. What is the percentage-to-fraction conversion technique for faster DI calculation?

   Memorize that common percentages equal simple fractions (e.g., 12.5% = 1/8, 16.66% = 1/6, 33.33% = 1/3, 25% = 1/4, 20% = 1/5), so you can multiply by the fraction instead of doing decimal multiplication.

2. List the fraction equivalents for 1/6, 1/7, 1/8, 1/9, and 1/11 as percentages (useful for speed calculation).

   1/6 ≈ 16.67%, 1/7 ≈ 14.28%, 1/8 = 12.5%, 1/9 ≈ 11.11%, 1/11 ≈ 9.09%.

3. How does 'approximation by rounding' speed up DI, and what is the caution?

   Round numbers to convenient values (e.g., 197 to 200, 48 to 50) to compute quickly. Caution: when answer options are very close, rounding too aggressively can pick the wrong option, so keep rounding proportional to the option gap.

4. What is the digit-grouping / first-significant-digits technique for comparing large numbers fast?

   Compare only the leading 2-3 significant digits and the magnitude (number of digits), ignoring trailing digits, since the most significant digits usually determine which value is larger or which ratio is bigger.

5. What is a fast method to compute percentage change between two values in DI?

   Percentage change = ((new - old) / old) x 100. For speed, compute the difference, divide by the base mentally using fraction approximations, and round; the base is always the original (older) value.

6. How do you quickly estimate a percentage like 'what percent is 37 of 80'?

   Use the fact that 80 x 0.5 = 40, so 37 is a bit under 50%; precisely 37/80 = 0.4625 = 46.25%. Anchor to easy benchmarks (10%, 25%, 50%) and adjust.

7. What is the technique of 'comparison without calculation' using cross-multiplication of ratios?

   To compare two fractions a/b and c/d, cross-multiply: a/b > c/d if a×d > b×c. This avoids computing the actual decimal values and is faster for ranking ratios.

8. In DI, what is 'data comparison' and what are common metrics used to compare entities?

   Data comparison means ranking or contrasting entities using metrics such as absolute value, percentage share, percentage change/growth, ratio, average, and rank. Choosing the right metric for the question is critical.

9. Why can the entity with the highest absolute growth differ from the one with the highest growth rate?

   Because growth rate = increase/base. A large entity can grow a lot in absolute terms yet have a small rate due to its big base, while a small entity can have a high rate from a modest absolute increase. Always match the metric to what is asked.

10. When comparing market shares across years, what must hold for a rising share to mean rising absolute value?

    Nothing guarantees it: a rising percentage share can coexist with falling absolute value if the overall total shrank. You must check the actual totals; share trend alone does not determine absolute trend.

11. What is the CAGR (Compound Annual Growth Rate) formula used in DI growth comparisons?

    CAGR = ((Final value / Initial value)^(1/n)) - 1, where n is the number of years. It gives the constant yearly rate that would grow the initial value to the final value.

12. How do you compute a weighted average, and where does it appear in DI?

    Weighted average = (sum of value×weight) / (sum of weights). It appears when combining group averages of different sizes, e.g., finding the overall average across departments with different headcounts.

13. What is the alligation rule and how does it speed up weighted-average DI problems?

    Alligation: for two groups with means M1 and M2 mixed to mean M, the ratio of quantities = (M2 - M) : (M - M1). It quickly finds mixing ratios or relative weights without setting up full equations.

14. What is the formula for simple average (arithmetic mean) and a quick check used in DI?

    Average = (sum of all values) / (number of values). Quick check: the average must lie between the minimum and maximum values; if your result falls outside that range, you made an error.

15. What is 'Set Selection Strategy' in CAT DILR and why is it decisive for scoring?

    It is the skill of scanning all available sets in the section and choosing which to attempt and in what order. It is decisive because CAT DILR has limited time and uneven difficulty, so picking easy/solvable sets first maximizes accuracy and score.

16. What is the recommended initial step in DILR set selection during the first few minutes?

    Spend the first 2-3 minutes scanning all sets to gauge difficulty, data type, and number of solvable questions, mentally tagging sets as 'attempt first', 'attempt later', or 'skip' before committing time to any single set.

17. What signals indicate a DILR set is a good 'easy/doable' pick?

    Clear and complete data, few variables/conditions, straightforward questions, a familiar format, and an evident solving path. Sets where you can structure the data quickly during the scan are strong picks.

18. What signals indicate a DILR set should be deprioritized or skipped?

    Heavy text/caselet with scattered conditions, many interdependent constraints, ambiguous or incomplete data, unfamiliar formats, or sets where you cannot see a path after the initial read. These are time sinks with low expected return.

19. What is the 'sunk cost' trap in DILR set selection and how do you avoid it?

    It is continuing to invest time in a hard set just because you already spent time on it. Avoid it by setting a per-set time limit (e.g., 8-12 minutes) and abandoning the set if you have not cracked the core arrangement by then, moving to a fresh set.

20. Why should you read all questions in a DILR set before solving, as part of set selection?

    Because the number and difficulty of questions determine the payoff. A hard set with 5-6 answerable questions may be worth more than an easy set with only 2 questions, so payoff-per-minute, not just difficulty, guides selection.

21. In set selection, how should accuracy be weighed given CAT's negative marking?

    Since wrong answers carry negative marks, prioritize sets where you can solve with high confidence. It is better to fully crack fewer sets accurately than to attempt many sets partially and risk multiple negatives from guesses.

22. What is a balanced target approach for number of sets attempted in a CAT DILR section?

    Rather than attempting all sets, aim to fully and accurately solve a selected number (commonly 3-4 of the available sets) with high accuracy, since complete accurate sets outscore many partial, error-prone attempts.

23. When a DI question gives totals and asks for a value 'closest to' an option, what does this signal about method?

    It signals that approximation is intended and acceptable. You should estimate rather than compute exact figures, choosing the nearest option, which saves significant time.

24. What is a key cross-format skill tested when a CAT set combines a Venn diagram with a table or caselet?

    The ability to translate between representations: extract counts from the diagram, reconcile them with table totals or caselet conditions, and apply inclusion-exclusion to fill unknowns, ensuring all subgroups sum to the stated totals.

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Data Interpretation (DILR) flashcards FAQ