1. Inference
Approximately 5 questions · Shares the single 30-minute budget across all five sections
What it tests. Evaluating the truth value of an inference drawn from stated facts, without letting outside knowledge skew the calculation.
Worked example. A factory closes to cut costs, 400 workers are made redundant, and six months later regional unemployment falls significantly. The inference some of the 400 found new work is Probably True; the inference the factory closed because workers lacked training is Insufficient Data.
Common traps. Confusing Probably True with Insufficient Data, and upgrading a Probably True to a full True when a single edge case could make it false.
How to handle it. Treat the text as an absolute boundary. If you must invent a mini-scenario to make the inference work, default to Insufficient Data. Absolute terms (all, never, always) are rarely True unless stated word-for-word.
2. Recognition of Assumptions
Approximately 8-9 questions · Part of the 30-minute pool
What it tests. Identifying whether a statement relies on an unstated presupposition to hold weight.
Worked example. A firm says it must train all trainees in generative AI to stay competitive. That AI will play a meaningful role in competition is an Assumption Made; that trainees are incapable of any digital technology is Assumption Not Made.
Common traps. Agreement bias (marking Assumption Made because you agree in real life) and confusing a future consequence with an underlying assumption.
How to handle it. Use the negation technique: reverse the assumption and reinsert it. If the argument collapses, the assumption is Made.
3. Deduction
Approximately 8-9 questions · Part of the 30-minute pool
What it tests. Strict syllogistic and conditional logic: whether a conclusion necessarily follows from the premises.
Worked example. All tier-one institutions require background checks; some entities that require background checks limit remote work. The conclusion some tier-one institutions limit remote work Does Not Follow, a classic Venn-diagram trap, because the overlap need not include the tier-one set.
Common traps. The common-sense override, and misreading some, which in formal logic means at least one and possibly all.
How to handle it. Convert statements into simple set mappings and never draw a link the premises do not structurally lock in.
4. Interpretation
Approximately 8-9 questions · Part of the 30-minute pool
What it tests. Judging whether a conclusion is logically derived from the evidence without any extrapolation.
Worked example. A study shows 80% of insomnia patients improved after a mindfulness course. The conclusion mindfulness helps the majority Follows; the conclusion it beats pharmaceutical treatment Does Not Follow, because drugs are never mentioned.
Common traps. Semantic slippage (deep-sleep duration does not validate feeling fully rested) and generalising a localised study to a wider population.
How to handle it. If the conclusion adds a new concept, a comparative term (better than, cheaper than) or a causal claim not in the evidence, select Does Not Follow.
5. Evaluation of Arguments
Approximately 8-9 questions · Part of the 30-minute pool
What it tests. Distinguishing strong arguments (both highly relevant and of major importance) from weak ones.
Worked example. On banning NDAs, the argument that it stops systemic misconduct being hidden from regulators is Strong; the argument that some executives find alternative paperwork mildly inconvenient is Weak.
Common traps. Personal-bias alignment (marking Strong because you agree politically) and confusing a true but trivial fact with a strong argument.
How to handle it. Strip emotional language and run a two-stage filter: is it entirely relevant to the core question, and is it a matter of major importance. Only then is it Strong.