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[ Mock Analysis Framework ]

Rule 1: Analysis time ≥ attempt time. Every wrong answer gets a tag: concept / calculation / trap / time / skip.

Rule 2: Re-attempt skipped questions untimed. If solved → avoidable skip. If not → concept gap.

Rule 3: Log patterns, not just scores. Next study block = top 3 failure tags only.

How to Analyse CAT Mocks: Error Taxonomy, Time Audits & the Adaptive Loop

Most aspirants treat mocks as score-checkers. Top 1% treat them as diagnostic instruments. This framework turns every mock into a remediation roadmap — free on AdaptHub.

The 5-tag error taxonomy

Every wrong/skipped answer gets exactly one tag. No "multiple issues" — pick the primary failure:

  • Concept Gap — Didn't know the rule/property/formula. Fix: targeted concept study + 5 adaptive drills mapped to your mastery-based progression tier.
  • Calculation Error — Arithmetic slip, sign error, unit mismatch. Fix: verification ritual per topic (sign check, unit check, boundary check).
  • Trap / Misread — Negation trap, root-cause mismatch, distractor matched (read our full distractor error taxonomy analysis). Fix: mandatory re-read check for that question type.
  • Time Sink — Correct but >3 min. Fix: heuristics / faster method / skip rule.
  • Avoidable Skip — Solved correctly untimed. Fix: selection heuristic / mental stamina.

The analysis session (same day, 90–120 min)

  1. Log section scores, accuracy, attempts, time spent per section.
  2. Re-attempt every wrong/skipped question untimed. Assign one tag.
  3. Re-solve all time-sink correct answers; find faster path.
  4. Re-read all RC passages you missed; mark inference vs detail vs tone errors.
  5. Enter tags into your log (or AdaptHub — tags auto-flow into next drill queue).

Weekly pattern review (every Sunday)

  • Top 3 tags by frequency → next week's drill focus.
  • Section attempt-order stability check (VARC first? DILR first?).
  • Sectional accuracy trends — is QA accuracy climbing, DILR stable?
  • Time-budget adherence: did you hit 40/40/40 or borrow from one section?

Where AdaptHub changes the loop

Manual logs work until they don't. AdaptHub's adaptive engine keeps practice inside your Zone of Proximal Development, tags distractor-style mistakes, and prioritises what to drill next — so the "action layer" of mock analysis is continuous, not a weekend spreadsheet. Learn the method on adaptive learning for CAT, or start free on the lifetime free pricing page.

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CAT Mock Analysis FAQs

How should I analyse a CAT mock test?+−
Spend at least as long analysing as attempting. Check section scores and time, classify every wrong answer (concept gap, calculation, trap/misread), review skipped questions you could have solved, and flag correct-but-slow items over ~3 minutes. Log patterns across mocks so the next study block targets real failure modes.
How many full-length CAT mocks do I need for 99 percentile?+−
Most serious 99%ile attempts involve roughly 20–35 full-length mocks, but volume without analysis plateaus scores. Quality of post-mock review and adaptive practice between mocks matter more than raw mock count.
When should I start taking CAT mocks?+−
Take an early diagnostic mock before the syllabus feels 'complete' to set a baseline. Use topic and sectional tests while building concepts, then increase full mocks weekly from roughly the mid-prep phase through the final two months.
What error types should I track in mock analysis?+−
At minimum: conceptual gaps, calculation/execution errors, and trap/distractor misreads. Add time-mismanagement and poor set selection for DILR. AdaptHub's distractor tagging automates part of this taxonomy during adaptive practice.
Is mock analysis more important than taking another mock?+−
Yes for most aspirants. An unanalysed mock only measures current level; analysis converts mistakes into a study plan. Toppers commonly spend 1–2× attempt time on review.