Quantitative Aptitude — Intermediate
Data Interpretation: the actual exam-relevant skill isn't calculation
Overview flags DI as carrying heavy weightage, and the intermediate-level insight worth internalizing directly: DI questions rarely require anything beyond basic arithmetic — the actual difficulty is reading the table/graph correctly and quickly under time pressure, not the math itself. Practicing DI specifically means practicing fast, accurate reading of tables, bar graphs, line graphs, pie charts, and caselets (a paragraph describing data instead of a table/chart) — many candidates who are individually strong at percentage/ratio calculation still lose time on DI specifically because they're slow at extracting the right numbers from the visual format first.
Mixture and Alligation — the shortcut method, not just the formula
For mixing two quantities at different rates/concentrations to get a target average, the alligation rule gives a fast ratio directly:
This is meaningfully faster under time pressure than setting up and solving a full algebraic equation for the same problem — worth practicing as its own distinct technique, since many candidates default to slower algebra out of habit even after learning the shortcut exists.
Time & Work — the work-rate-per-day framework
The core reframing that makes Time & Work problems tractable: convert "A can do a job in 10 days" into "A does 1/10 of the job per day" — this turns the problem into simple addition/subtraction of rates, rather than needing a separate formula per problem type. Combined work: if A does 1/10/day and B does 1/15/day, together they do (1/10 + 1/15) = 1/6 per day, meaning 6 days to finish together. Pipes and cisterns problems (a common variant) use the exact same framework — an "inlet pipe" is a positive work rate, an "outlet pipe" (draining) is a negative one.
Number Series — pattern recognition, systematically, not by guessing
Rather than staring at a series hoping to spot the pattern, check systematically in this order: (1) constant difference between consecutive terms, (2) constant ratio (geometric), (3) difference-of-differences (second-order arithmetic pattern), (4) alternating pattern (two interleaved sequences), (5) a pattern based on position (squares, cubes, or a term's relationship to its index). Working through this checklist in order, rather than randomly trying operations, is meaningfully faster under exam time pressure than unstructured pattern-hunting.
Quant-based reasoning: Mains-level hybrid questions
Overview notes Mains shifts toward combining quant with reasoning — concretely, this means questions where you need to extract a numeric relationship from a reasoning-style puzzle (a seating arrangement with numeric constraints, a data-sufficiency question requiring you to determine whether given information is enough to answer, without necessarily solving it fully). Data Sufficiency specifically is worth deliberate practice as its own sub-skill: the goal is judging whether the given statements are sufficient to answer, not computing the actual numeric answer — a genuinely different task from a standard calculation question, and a common source of wasted time when candidates solve the problem fully instead of just judging sufficiency.
Approximation-based elimination for DI "which is highest/lowest" questions
For a DI question asking which option is highest/lowest among several close values, exact calculation is usually unnecessary and slower than approximation — round each value to a convenient level of precision (nearest whole number, nearest 5, depending on how close the options are) and eliminate options that are clearly not the highest/lowest before doing any precise calculation on the remaining close contenders, if any calculation is even still needed at that point.