Test Partnership-style familiarization: study guide

Commercial assessment-provider familiarization · suite apt-365-test-partnership-style-familiarization · generated 2026-09-15T17:50:33.134Z

Title
Test Partnership-style familiarization: study guide
Generated
2026-09-15T17:50:33.134Z
Fixture/version
apt-365-test-partnership-style-familiarization
Sector
Commercial assessment-provider familiarization
Guide version
v2

Private practice result. Not an official exam certificate, employer decision, hiring signal, admissions decision, or guaranteed outcome. Scores stay on this device unless you export them.

Answer keys and scoring logic stay server-side and are never included in any download or export.

How to use this guide

This file contains the whole study outline for this suite: every skill it draws on, the full lesson for each of those skills, worked examples, practice tips, a glossary, and where each piece of material comes from. Nothing here is a summary of a page you still have to visit.

  1. Read the skills section end to end once, without timing yourself.
  2. Work the guided practice mode for the suite, using the practice tips as a checklist.
  3. Move to the mini-test only when guided practice feels unhurried.
  4. Sit the full simulation last, once, in the conditions you expect on the day.

Practice attempts are stored on the device you used, never on an account. Exporting a result is the only way anything leaves that device.

Practice modes and durations

Practice modes for Test Partnership-style familiarization
ModeDurationWhat it is for
Guided practice15 minutesUntimed, with feedback after every item.
Mini-test18 minutesA short timed set for checking pace.
Full simulation45 minutesFull length and full time, in one sitting.

Skills covered, in full

This suite draws on 5 skill constructs. Each one below carries its complete lesson.

Critical thinking

Evaluating evidence, assumptions, arguments, credibility, and alternative explanations.

Critical thinking assessments ask you to take an argument apart: what is being concluded, what it rests on, what evidence would settle it, and whether a proposed conclusion actually follows. Published critical-thinking batteries typically run five task types - inference, recognition of assumptions, deduction, interpretation, and evaluation of arguments - and they are deliberately built so that agreeing with a conclusion and judging the argument as strong come apart. The construct is heavily weighted in policy analysis, audit, legal, investigative and graduate selection, and it is the same skill that stops a plausible chart from turning into a bad decision. Practice stays on this device; there is no account and nothing is uploaded unless you export it.

What you should be able to do after this lesson:

  1. State an argument's conclusion in your own words before evaluating it, and identify which sentences are premises and which are background.
  2. Use the negation test to separate a required assumption from a statement that would merely strengthen the argument.
  3. Distinguish validity from truth, and identify affirming the consequent as distinct from the valid modus tollens form.
  4. Compute a posterior probability on a screening example and explain why the rate of true positives among all positives is far lower than intuition suggests.
  5. Generate at least two alternative explanations - selection, reverse causation, a common third factor - for any claimed causal effect, and name the comparison that would rule them out.
  6. Judge argument strength on relevance and directness rather than on agreement, including marking arguments you personally reject as strong.

Worked examples and pitfalls

The negation test finds assumptions; nothing else does: Argument: 'The council should fit bin sensors across the district. In the trial depot they cut collection trips by a fifth.' Candidate assumption A: 'The trial depot's waste pattern is broadly representative of the rest of the district.' Negate it - suppose the trial depot is nothing like the rest of the district - and the argument collapses, because a result that does not transfer supports nothing about the district. So A is a required assumption. Candidate assumption B: 'Bin sensors are the cheapest available technology for this purpose.' Negate it - suppose they are the most expensive - and the argument still stands as given, since it argued from a reduction in trips, not from cost. B is not required; it would strengthen a cost-based argument that was never made. Candidate C: 'Fewer collection trips reduce total operating cost.' Negate it and the recommendation loses its point, so C is required too, even though the argument never mentions cost. That last case is the one candidates miss, because the required assumption is what bridges the evidence to the recommendation, and bridging assumptions are by definition unstated. The failure mode across this whole item type is picking statements that support the conclusion instead of statements the argument cannot survive without.

Base rates: 90 percent accurate, 15 percent right: A production line runs an automated defect test. Defects occur in 1 percent of units. The test flags 90 percent of genuinely defective units, and wrongly flags 5 percent of good units. A unit has just been flagged - how likely is it to be defective? Work in whole units rather than probabilities. Take 10,000 units: 100 are defective and 9,900 are good. Of the 100 defective, the test flags 90. Of the 9,900 good, it wrongly flags 5 percent, which is 495. Total flags: 90 + 495 = 585. Of those, 90 are genuine, so the answer is 90 / 585 = 15.4 percent. Better than the 1 percent base rate, and nowhere near the 90 percent that intuition offers. The error has a name - confusing the probability of a flag given a defect with the probability of a defect given a flag - and it has a practical consequence: the rework queue has to be sized for 585 units a batch, not 100, and 495 of the 585 units sitting in it are perfectly good. Whenever a test, screening rule or model accuracy figure appears in an item, ask how many of the negatives there are, because with a rare condition the false positives from a large clean population swamp the true positives from a small affected one.

Three alternative explanations, and the comparison that settles it: Claim: 'Employees who attended the optional resilience workshop took 30 percent fewer sick days last year, so the workshop works.' Alternative one, selection: attendance was optional, so the people who signed up may have been the healthier and more engaged to begin with, and would have taken fewer sick days regardless. Alternative two, reverse direction: employees who were frequently unwell were the least able to attend a full-day workshop, so illness determined attendance rather than the other way round. Alternative three, a common third factor: the workshop ran on Thursday afternoons at head office, so attendance largely tracks being an office-based rather than shift-based worker, and shift workers take more sick leave for reasons that have nothing to do with resilience training. What would settle it: randomly assigning the offer to half the workforce and comparing the two groups. Failing that, the cheapest useful check already exists in the payroll data - compare attendees' and non-attendees' sick days in the year before the workshop. If attendees were already 30 percent lower, selection is doing the entire job. The habit worth building is to name the comparison group before you accept any before-and-after number.

Deduction: affirming the consequent versus modus tollens: Rule: 'If an invoice is over 10,000 euro, it requires two signatures.' Argument A: 'This invoice has two signatures, therefore it is over 10,000 euro.' Invalid - this is affirming the consequent. The rule makes two signatures necessary for large invoices; it says nothing that prevents a cautious manager from double-signing a 400 euro invoice, so a two-signature invoice of any size is consistent with the rule. Argument B: 'This invoice has only one signature, therefore it is not over 10,000 euro.' Valid - this is modus tollens, denying the consequent to deny the antecedent, and it holds assuming the rule was followed. Argument C: 'This invoice is not over 10,000 euro, therefore it does not have two signatures.' Invalid again, denying the antecedent. Two further points that deduction items test directly. First, validity is about form alone: 'All banks close on Sundays; Riverton Mutual is a bank; therefore Riverton Mutual closes on Sundays' is perfectly valid even if the first premise is false, and a valid argument with a false premise can deliver a false conclusion. Second, in these items you must accept the premises as given even when you know them to be untrue, because the question is whether the conclusion follows, not whether it is true.

Interpretation: what a survey figure does and does not license: Data: all 1,200 employees of a firm were surveyed. 62 percent said they would accept a four-day week at 90 percent pay. Of those who said yes, 71 percent were under 35. Conclusion one: 'A majority of this firm's employees would accept the trade.' This follows - 62 percent of a complete census of the firm is a majority, and the conclusion is properly limited to this firm. Conclusion two: 'A majority of the firm's under-35 employees would accept the trade.' This does not follow, and the arithmetic shows why. Sixty-two percent of 1,200 is 744 accepters, and 71 percent of 744 is about 528 accepters aged under 35. That is the composition of the accepters, not the acceptance rate within the under-35 group, and without knowing how many under-35s the firm employs the rate is undetermined: if there are 900, the rate is 528 / 900 = 59 percent; if there are 600, it is 88 percent; if there were 1,100 the rate would be below half. Conclusion three: 'The firm should move to a four-day week.' This does not follow either - a stated preference about pay says nothing about output, shift cover, customer hours or cost. Notice that conclusion two is the base-rate error from the screening example, wearing survey clothing.

Strong and weak arguments on the same question: Question: should the agency publish raw inspection scores for every site? Strong argument for: 'In the neighbouring authority, publication was followed by a measurable fall in repeat violations, which is the stated aim of the inspection regime.' It is directly about this decision, it addresses the regime's own objective, and it offers evidence - and if true it would change your view. Weak argument for: 'Yes, because transparency is always good.' Sweeping, unsupported, and it would apply identically to publishing anything at all, which is the tell. Strong argument against: 'Raw scores omit the severity weighting, so a site with one critical failure can rank above a site with six minor ones, and a member of the public cannot see the difference.' Specific, mechanistic, directly about the proposal, and it would change your view. Weak argument against: 'No, because businesses will object.' It may be true and it may matter politically, but it does not bear on whether publication achieves the regime's aim, and no evidence is offered. Two tests separate strong from weak: is the argument about the exact question asked, and would accepting it change the decision? Note that you can hold a firm personal view on publication and still be required to mark the argument on the other side as the strong one - that split is what the item type is measuring.

How to practise this skill

  • Negate every candidate assumption out loud. If the argument survives the negation, it was never an assumption, however supportive it sounds. This single habit converts the assumption item type from guesswork into a mechanical check.
  • Write the conclusion in your own words before reading any option. Half of the wrong answers on inference and evaluation items are responses to a conclusion the argument never reached.
  • Ask 'percentage of what?' on every percentage in the stimulus and reconstruct the denominator in whole units. Base-rate and composition errors both dissolve the moment you write out counts instead of rates.
  • Deliberately practise marking arguments you disagree with as strong and arguments you agree with as weak. Assessments in this construct are built to catch agreement masquerading as evaluation, and the effect is largest on politically loaded stimuli.
  • For any causal claim, write two alternatives - selection and a third factor - and name the comparison group that would rule them out, before you decide whether the evidence supports the claim.
  • Log wrong answers by task type rather than by topic: inference, assumption, deduction, interpretation, evaluation. Candidates are rarely weak across all five, and the profile tells you where the next hour of practice belongs.

Glossary

Conclusion
The claim an argument is trying to establish. It is not always last, is often signalled by therefore, so, or should, and locating it correctly determines every subsequent judgement about the argument.
Assumption
An unstated premise the argument requires in order to work. Identified by negation: negate it and a genuine assumption brings the argument down, while a merely helpful statement leaves it standing.
Validity and soundness
An argument is valid when the conclusion cannot be false while the premises are true, which is a property of form alone. It is sound when it is valid and the premises are actually true.
Affirming the consequent
The invalid pattern 'if P then Q; Q; therefore P'. It is the most common deductive distractor because it differs from the valid modus tollens form by only the position of a negation.
Base rate
How common something is in the population before any test or evidence is applied. Ignoring it makes accurate-sounding tests appear far more informative than they are when the condition is rare.
Confounder
A third factor associated with both the supposed cause and the outcome, capable of producing the entire observed relationship on its own. Ruled out by randomisation or by an explicit comparison group.
Selection effect
A difference between groups created by how people entered them rather than by the treatment under study. Optional programmes and voluntary surveys are where it appears most often.
Falsifiability
The property of a claim that some observation could show it to be wrong. A claim compatible with every possible result carries no information, which is why 'what would change your mind?' is a diagnostic question.

Where this material comes from

  • Worked items written for Novus Learn. The arguments, survey figures, defect-test numbers and evaluation options above are original and invented for this lesson; no published or copyrighted test item is reproduced.
  • The five task types named in the summary - inference, assumption, deduction, interpretation, evaluation of arguments - describe a structure used publicly across several critical-thinking assessments; no affiliation with any publisher is claimed or implied.
  • Terminology follows standard, widely published usage in introductory logic and research methods - validity, soundness, affirming the consequent, base rate, confounder, selection effect.
  • Novus Learn aptitude construct registry (catalog seed) for the construct scope and the suite mapping shown in the related links.
  • Public educational framing only - not affiliated with any official exam board, publisher or employer.

Educational preparation only. Novus Learn does not administer official exams and does not guarantee scores or hiring outcomes.

Numerical reasoning

Arithmetic, fractions, percentages, ratios, rates, estimation, word problems, and number relationships.

Numerical reasoning is the ability to take a small set of supplied numbers (a price list, a staffing table, a fuel figure), and reach a defensible answer in around ninety seconds without a formula sheet. It is the most widely used quantitative section in graduate, management and public-sector screening, and it appears in banking, retail, armed forces and healthcare entry batteries alike. The arithmetic itself is deliberately ordinary: percentages, ratios, rates and averages. What is actually being measured is whether you pick the right operation quickly, keep the units straight, and answer the question that was asked rather than the one you started computing. Practice here is device-local: no account, and nothing leaves this device unless you export it.

What you should be able to do after this lesson:

  1. Move between fractions, decimals, percentages and ratios on sight, and pick whichever form makes a given item fastest (12.5 percent as one eighth, 33.3 percent as one third).
  2. Apply percentage change in both directions, including recovering an original figure from a post-increase total, and combine successive changes multiplicatively rather than by adding them.
  3. Split a total in a stated ratio by counting parts first, and work backwards from a stated difference between two shares.
  4. Solve rate problems (speed, unit price, consumption, combined work rates) by carrying units through every intermediate line so the units of the answer prove the method.
  5. Produce a one-significant-figure estimate before computing, and use it to eliminate the distractors built from the common wrong operations.
  6. Read a multi-step stem and name, in one sentence, the single quantity the final question asks for before touching the numbers.

Worked examples and pitfalls

Reverse percentages: the item most candidates get backwards: A subscription price rose by 15 percent and now stands at 57.50 pounds. What was it before? The correct move is to divide, not subtract: the new price is 115 percent of the old, so the old price is 57.50 / 1.15 = 50.00. Check it forwards: 15 percent of 50 is 7.50, and 50 + 7.50 = 57.50. The tempting wrong answer takes 15 percent of the NEW figure, 0.15 x 57.50 = 8.625, and reports 48.88. That distractor is always on the option list because it is what most people do under time pressure, and it is wrong by 2.25 percent, small enough to look plausible. The same asymmetry drives the successive-change item: a price that rises 20 percent and then falls 20 percent does not return to where it started. Multiply the factors: 1.20 x 0.80 = 0.96, a net fall of 4 percent. Starting at 500 pounds you get 600 then 480, not 500. Percentages compose by multiplication; they never add.

Ratio splits: count the parts before you divide: A 4,830 pound budget is split between three teams in the ratio 3:5:6. Add the parts first: 3 + 5 + 6 = 14. One part is 4,830 / 14 = 345. The shares are 3 x 345 = 1,035, 5 x 345 = 1,725 and 6 x 345 = 2,070, and they sum back to 4,830, which is the check you should always run. Two classic failures. The first is dividing by 3 because there are three teams. That gives 1,610 each and ignores the ratio entirely. The second is treating 5 as a fraction and computing five sixths or five fourteenths of something other than the total. The more interesting version of this item gives you a difference instead of the total: 'the second team receives 690 pounds more than the first, what is the whole budget?' The difference between the shares is 5 - 3 = 2 parts, so one part is 690 / 2 = 345, and the budget is 14 x 345 = 4,830. Same number, reached from the other end, and the arithmetic is trivial once you have made the parts explicit.

Rates and units: 2 h 15 min is 2.25, not 2.15: A delivery van covers 174 km in 2 hours 15 minutes. Average speed is distance over time, and the time must be in hours: 15 minutes is 15/60 = 0.25 h, so 174 / 2.25 = 77.3 km/h. Type 2.15 into the calculator instead and you get 80.9 km/h: an error of roughly 4.7 percent that sits comfortably inside the plausible range and will match one of the options. Now extend it. The van consumes 8.6 litres per 100 km, so the trip needs 174 x 8.6 / 100 = 14.964 litres, and at 1.48 pounds per litre that is 14.964 x 1.48 = 22.15 pounds. Notice the units doing the work: (km) x (L / 100 km) leaves litres; (L) x (pounds / L) leaves pounds. If your intermediate line has km still attached at the end, you have divided when you should have multiplied. Write the unit next to every number and the method checks itself.

Unit pricing: normalise before you compare: Three pack sizes of the same fluid. Pack A: 750 ml for 3.60 pounds. Pack B: 2 litres for 9.40. Pack C: 1.5 litres for 7.20. Convert all three to price per litre. A: 3.60 / 0.75 = 4.80 per litre. B: 9.40 / 2 = 4.70. C: 7.20 / 1.5 = 4.80. So B is cheapest by 10p a litre, and A and C are identical despite looking like different deals. The 'bigger pack is cheaper' heuristic happens to hold here but is not a rule, and test writers know it. Half of these items are built specifically so the largest pack loses. Now add the multibuy that these questions love: pack A is on three-for-two. Three packs give 2.25 litres for the price of two, 7.20 pounds, which is 7.20 / 2.25 = 3.20 per litre and beats everything. The trap in the multibuy version is dividing by the number of packs paid for rather than the volume received.

Combined work rates: add rates, never times: Printer A completes a 3,000-page run in 50 minutes; printer B completes the same run in 75 minutes. Running together, how long? Convert to rates: A prints 3,000 / 50 = 60 pages per minute, B prints 3,000 / 75 = 40 pages per minute, and together they print 100 pages per minute, so the job takes 3,000 / 100 = 30 minutes. Verify by counting output: in 30 minutes A produces 1,800 pages and B produces 1,200, which is 3,000 exactly. The two wrong answers you will see on the option list are 62.5 minutes (the average of 50 and 75) and 125 minutes (the sum). Both are impossible on inspection: two machines working together must finish faster than the faster machine alone, so any answer above 50 minutes is wrong before you compute anything. The general form is 1 / (1/50 + 1/75), and it is worth being able to write that line directly, but the sanity bound catches the error faster than the algebra does.

Estimate first, then compute: killing distractors in ten seconds: 'A department spent 847,300 pounds in 2024. In 2025 the budget fell by 12.5 percent. What was the 2025 spend?' Options: 741,387.50 / 953,212.50 / 105,912.50 / 762,570. Estimate before anything else: 12.5 percent is exactly one eighth, one eighth of roughly 850,000 is roughly 106,000, so the answer is roughly 744,000. That single line eliminates three options. 953,212.50 applied the change upwards. 105,912.50 is the size of the reduction, not the resulting spend: the 'answered the wrong question' distractor, and the most commonly selected wrong option on items of this shape. 762,570 is a 10 percent cut, planted for anyone who misread the rate. Exact working: 847,300 x 7/8 = 5,931,100 / 8 = 741,387.50. Doing it as a fraction avoids the decimal multiplication altogether. Learn the fraction equivalents cold (12.5 percent is 1/8, 16.7 percent is 1/6, 37.5 percent is 3/8, 62.5 percent is 5/8) because a fraction turns most percentage items into one division.

How to practise this skill

  • Memorise the fraction-to-percentage table up to eighths and twelfths. Almost every 'nasty' percentage on these tests is a clean fraction in disguise, and the fraction route is two or three times faster than decimal multiplication.
  • Write the unit beside every intermediate number, including the ones you keep in your head. Most numerical errors on timed sections are unit errors, not arithmetic errors, and units are the only cheap way to catch them.
  • Rehearse reverse percentages as their own drill until dividing by 1.15 feels more natural than subtracting 15 percent. It is a single, identifiable technique that accounts for a disproportionate share of lost marks.
  • Before selecting, re-read the last clause of the stem out loud. 'By how much did it fall' and 'what was it after the fall' have different answers, and both are always on the option list.
  • Keep an error log with four columns (misread the question, wrong operation, unit slip, arithmetic slip), and tally which one you actually commit. Three sessions is usually enough to show that one column dominates, and that is the column to train.
  • Work untimed until your method is stable, then add the clock in stages: generous, then realistic, then 20 percent tighter than the real test. Attempts stay on this device, so a slow first pass costs nothing.

Glossary

Percentage point
The arithmetic difference between two percentages. A rate moving from 4 percent to 5 percent rises by one percentage point but by 25 percent in relative terms; questions specify which they want and the two answers are both on the option list.
Reverse percentage
Recovering an original amount from a figure that already includes a percentage change, by dividing by the multiplier (1.15 for a 15 percent rise, 0.88 for a 12 percent fall) rather than subtracting the percentage from the new figure.
Multiplier (decimal factor)
The single number a quantity is multiplied by to apply a percentage change: 1.20 for plus 20 percent, 0.80 for minus 20 percent. Successive changes are handled by multiplying the factors, which is why plus 20 then minus 20 gives 0.96, not 1.
Ratio part
One unit of a ratio split. Dividing the total by the sum of the ratio terms gives the value of one part; every share and every difference between shares is then a whole number of parts.
Unit rate
A quantity expressed per one of something: price per litre, pages per minute, litres per 100 km. Comparisons are only valid once every option has been converted to the same unit rate.
Combined rate
The sum of two or more individual rates working simultaneously. Times cannot be added or averaged; only rates add, and the combined time is the total work divided by the combined rate.
Significant figure estimate
Rounding every input to one meaningful digit to get an approximate answer in a few seconds. Its purpose is not accuracy but elimination: it removes any option that is off by a factor or has the sign of the change wrong.
Distractor
A wrong option written deliberately to match a specific predictable error: subtracting instead of dividing, reporting the change instead of the result, averaging instead of combining rates. Recognising the pattern is often faster than recomputing.

Where this material comes from

  • All worked figures above were written and checked for Novus Learn. Every division, ratio split and rate calculation in this lesson was verified by recomputing it in the reverse direction.
  • Conventions only (percentage point, unit rate, significant figures) cross-checked against standard public references such as the Wikipedia articles 'Percentage', 'Ratio' and 'Rate (mathematics)'. No item text is drawn from any published test.
  • Novus Learn aptitude construct registry (catalog seed) for construct scope and suite mapping.
  • Public educational framing only: not affiliated with any official exam board, publisher or employer, and no copyrighted test item is reproduced.

Educational preparation only. Novus Learn does not administer official exams and does not guarantee scores or hiring outcomes.

Verbal reasoning

Drawing conclusions from written information without relying on outside assumptions.

Verbal reasoning is the discipline of answering strictly from a passage: deciding whether a statement is True, False, or Cannot Say on the evidence given, and refusing to import anything you happen to know about the topic. It is the workhorse construct in graduate and civil-service screening, banking and consulting sifts, and language-focused public-service batteries, where a passage about parcel volumes or grant conditions is followed by four statements to classify. The same discipline is what stops a contract review, a grant assessment or an incident summary from quietly acquiring facts nobody wrote down. Practice here is device-local: no account, and nothing leaves this device unless you export it.

What you should be able to do after this lesson:

  1. Classify a statement as True, False, or Cannot Say, and state in one sentence which words in the passage force the classification.
  2. Explain the difference that costs the most marks: 'Cannot Say' means undetermined by the passage, while 'False' means contradicted by it.
  3. Spot quantifier drift between passage and statement (all, some, most, only, none) and show why 'all A are B' never licenses 'all B are A'.
  4. Refuse a causal upgrade: recognise when a passage reports co-occurrence or sequence and a statement claims cause.
  5. Separate what a passage asserts from what it reports somebody else asserting, and classify statements about each correctly.
  6. Do the small arithmetic hidden inside verbal items - percentage changes, fractions of a stated total - without leaving the passage for outside data.

Worked examples and pitfalls

The three-way rule on one short passage: Passage: 'The Riverton depot handled 4,200 parcels in March, a 12 percent increase on February. A night shift was introduced in January; in March it processed 40 percent of the parcels the depot handled.' Now take four statements. (1) 'The depot handled 3,750 parcels in February.' February is March divided by 1.12: 4,200 / 1.12 = 3,750 exactly, so this is True - the passage determines it even though the number is not printed. (2) 'The night shift caused the March increase.' Cannot Say. The passage puts the night shift and the increase in the same depot in the same period; it never claims one produced the other, and it never denies it either. Most candidates mark this False, reasoning correctly that correlation is not causation but then choosing the wrong label: False is reserved for statements the passage contradicts. (3) 'The night shift processed more than 1,700 parcels in March.' Forty percent of 4,200 is 1,680, which is not more than 1,700, so this is False - contradicted by arithmetic on the passage's own figures. (4) 'The depot handled more parcels in March than in January.' Cannot Say: January is mentioned only as the month the shift started, and no January volume is given.

Quantifier drift and illicit conversion: Passage: 'All accredited suppliers submit quarterly audits. Some suppliers in the northern region are accredited.' Statement A: 'Some suppliers in the northern region submit quarterly audits.' True, and it is worth seeing why the chain holds: at least one northern supplier is accredited, and every accredited supplier submits, so at least one northern supplier submits. Statement B: 'Every supplier that submits quarterly audits is accredited.' This reverses the first sentence. 'All accredited suppliers submit' leaves the door wide open for unaccredited suppliers to submit as well - perhaps voluntarily, perhaps under another rule - so the answer is Cannot Say. Turning 'all A are B' into 'all B are A' is called illicit conversion and it is the single most productive trap in this format, because the reversed sentence sounds like a paraphrase. Statement C: 'No unaccredited supplier submits quarterly audits' is the same reversal wearing a negative coat, and it is Cannot Say for the same reason. Statement D: 'All northern suppliers submit quarterly audits' is also Cannot Say: 'some are accredited' says nothing about the rest.

Asserted versus reported: Passage: 'The committee's report claims that the scheme cut waiting times by a third. Two of the four regional boards have disputed that figure.' Statement A: 'The scheme cut waiting times by a third.' Cannot Say. What the passage asserts is that a report claims this; the claim's truth is never settled, and the dispute does not settle it either. Statement B: 'At least two regional boards disagree with the report's waiting-time figure.' True, and note 'at least' - the passage says two disputed it, and two of four disputing is consistent with 'at least two'. Statement C: 'All four regional boards accept the figure.' False, directly contradicted. Statement D: 'The report is wrong.' Cannot Say. This item type appears constantly in policy and diplomacy passages, where a paragraph stacks a claim, a source, and a reaction, and the reader has to keep three different truth-conditions apart. The reliable habit is to underline the reporting verb - claims, argues, estimates, alleges, projects - and remember that everything downstream of it belongs to the source, not to the passage.

Percentages are not symmetric: Passage: 'Membership fell from 8,000 to 6,000 over two years, then recovered by 25 percent in the third year.' Statement: 'Membership at the end of year three was higher than at the start.' The fall is 2,000 on a base of 8,000, which is 25 percent. The recovery is 25 percent of the new base: 6,000 x 1.25 = 7,500. That is below 8,000, so the statement is False. The trap is elegant, because a 25 percent fall followed by a 25 percent rise feels like it should cancel. It does not: to get back from 6,000 to 8,000 you need a 33.3 percent rise, since 2,000 / 6,000 = 0.333. Whenever a verbal item states a change as a percentage, write down what the percentage is a percentage of before you touch it. A related version supplies the recovery as an absolute number instead - 'recovered by 2,000 members' - which does return the total to 8,000, and candidates who answered the first version from memory get the second one wrong.

Verbal analogies: name the relation as a sentence: Item: 'ANTISEPTIC is to INFECTION as ___ is to ___.' Options: (a) vaccine : immunity, (b) insulation : heat loss, (c) medicine : illness, (d) bandage : wound. Write the stem relation as a full sentence first: 'An antiseptic is applied in order to prevent an infection from occurring.' Now test each option against that exact sentence. Option (a) runs the other way - a vaccine is given to produce immunity, not to prevent it. Option (c) is the right family but the wrong specificity: medicine typically treats an illness that has already started. Option (d) is applied after the wound exists. Option (b) fits precisely: insulation is applied in order to prevent heat loss from occurring. The general method is the same on the simpler item types. 'BOOK is to LIBRARY as PAINTING is to ___' has canvas (the material), artist (the maker), and gallery (the place a collection is kept and shown) among its options; all three are genuine relations to 'painting', and only the third matches the stem sentence. Options in analogy items are chosen to be true statements about the words, just not the stated relation.

Two premises with 'some' prove nothing: Argument: 'Some depot managers are qualified engineers. Some qualified engineers hold a rigging certificate. Therefore some depot managers hold a rigging certificate.' This is invalid, and the way to prove it is a counter-model rather than an argument. Let the depot managers be Ana and Ben; let the qualified engineers be Ben and Cara; let the certificate holders be Cara alone. Premise one holds: Ben is a manager and an engineer. Premise two holds: Cara is an engineer with the certificate. The conclusion fails: neither Ana nor Ben holds the certificate. Since a single consistent world makes both premises true and the conclusion false, the argument cannot be valid, so in a True / False / Cannot Say framing the conclusion is Cannot Say. Two premises that both begin 'some' never combine into a conclusion, because 'some' gives you an overlap without telling you where the overlap sits. Contrast a valid pair: 'All accredited labs are inspected annually. No inspected facility is exempt from the fee.' Every accredited lab is inspected, and no inspected facility is exempt, so no accredited lab is exempt - True.

How to practise this skill

  • Answer from the passage even when you know the subject. Candidates with a background in the topic score worse on verbal items than they expect, because their own knowledge quietly supplies the missing premise that turns a Cannot Say into a True.
  • Run the two-worlds test on every candidate 'Cannot Say': can you imagine a world where all the passage's sentences hold and the statement is true, and another where they hold and it is false? If both, it is Cannot Say. If only the false world exists, it is False.
  • Underline the quantifiers and hedges in the statement (all, some, only, most, may, must, likely) and find their counterparts in the passage. Roughly half of the wrong answers in this construct come from a single word swapped between the two.
  • Budget about 25 to 30 seconds per statement rather than per passage, and read the passage once for structure before touching the statements. Re-reading the whole passage for each statement is what causes candidates to run out of time on the last set.
  • Keep a wrong-answer log with one label per error: quantifier, causation, reported-versus-asserted, arithmetic, outside knowledge. A clear pattern almost always emerges within about forty items, and it is usually a single label.
  • Work untimed until the three-way rule is automatic, then add the clock. Attempts are stored on this device only, so a slow first pass through a passage set costs you nothing but the time you spend on it.

Glossary

Entailment
A statement is entailed by a passage when it cannot be false while every sentence of the passage is true. Entailment is the only thing that earns a 'True' in this format; being plausible, likely, or well known does not.
Cannot Say
The verdict for a statement the passage neither entails nor contradicts. It is a claim about the passage, not about the world, which is why a statement you know to be true in real life can still be Cannot Say.
Quantifier
A word fixing how much of a group a claim covers: all, most, some, few, none, only. Swapping one quantifier for another changes the logical content completely while barely changing how the sentence reads.
Illicit conversion
The invalid move from 'all A are B' to 'all B are A', or from 'if P then Q' to 'if Q then P'. It preserves the words and destroys the logic, which is why converted sentences make such effective wrong answers.
Counter-model
A concrete, consistent scenario in which the premises hold and the conclusion fails. Producing one is the fastest possible proof that an argument is invalid, and it takes two or three named individuals.
Hedge
A qualifier such as may, could, is expected to, or is associated with. A hedged sentence in a passage cannot support an unhedged statement, and an unhedged passage sentence is not weakened by a hedged statement.
Reporting verb
A verb such as claims, argues, estimates, or alleges that attributes the following content to a source. Everything downstream of it is the source's assertion, and the passage takes no position on it.
Analogy relation
The specific link between the two stem words in an analogy item - tool and user, item and container, action and purpose. Naming it as a full sentence before reading the options removes almost all of the guesswork.

Where this material comes from

  • Worked items written for Novus Learn. Every passage, statement set and figure above is original and invented for this lesson; no published or copyrighted test item is reproduced.
  • Terminology follows standard, widely published usage in introductory logic and assessment writing - entailment, quantifier, illicit conversion, counter-model.
  • Novus Learn aptitude construct registry (catalog seed) for the construct scope and the suite mapping shown in the related links.
  • Public educational framing only - not affiliated with any official exam board, publisher or employer.

Educational preparation only. Novus Learn does not administer official exams and does not guarantee scores or hiring outcomes.

Situational judgment

Evaluating workplace responses against role-relevant principles.

Learn a repeatable way to compare workplace responses: establish the facts, identify duties and risks, respect role boundaries, then choose a proportionate first action. This is educational preparation, not an official scoring guide.

What you should be able to do after this lesson:

  1. Separate facts stated in a scenario from assumptions that the scenario does not support.
  2. Rank response options by immediate risk, policy or role obligations, proportionality, and follow-through.
  3. Explain why a strong first action is better than passive, punitive, or unauthorized alternatives.

Worked examples and pitfalls

Worked scenario: an unverified safety concern: A colleague reports a possible equipment fault while a deadline is approaching. First distinguish the known fact, the report, from the unverified cause. A strong response protects people and affected work, checks the concern through the right channel, tells the relevant lead, and records what was done. Ignoring the report underreacts; shutting down unrelated work or accusing someone before checking the facts overreacts.

Method: facts, duties, risks, response: Write four short notes before ranking options: what is known, who may be affected, which duty or boundary applies, and what safe next step is available now. Prefer an action that addresses the immediate issue and creates useful follow-through. Do not reward an option merely because it sounds decisive.

How to practise this skill

  • Answer the question asked: best first action, worst action, or complete response are different tasks.
  • Check whether an option acts within the person's authority and escalates only as far as the risk requires.
  • When two options look reasonable, prefer the one that gathers missing facts and communicates ownership.

Glossary

Proportionality
Matching the urgency and scope of a response to the evidence, likely impact, and authority available.
Role boundary
The limit of what a person may decide or do without approval, specialist help, or escalation.
Follow-through
Confirming ownership, recording the decision, and checking that the issue was actually resolved.

Where this material comes from

  • Novus Learn original situational-judgment suite scenarios and published construct mapping.
  • Novus educational framework: facts, duties, risks, role boundaries, proportional action, and follow-through.

Educational preparation only. Novus Learn does not administer official exams and does not guarantee scores or hiring outcomes.

Inductive reasoning

Identifying general rules from examples, sequences, and observations.

Inductive reasoning is the ability to look at a handful of examples (a number series, a set of observations, a table of past decisions), and propose the rule that generated them, while staying honest about the fact that finished evidence never fully proves a rule. It carries most of the weight in graduate ability batteries, analyst and intelligence screening, and college placement testing, and it is what a technician does when three failures on the same line suggest a pattern rather than three coincidences. The construct rewards two opposite habits at once: generate candidate rules quickly, then try hardest to break the one you like. Everything you practise here is device-local unless you export it.

What you should be able to do after this lesson:

  1. Compute first and second differences on a numeric series and use them to distinguish arithmetic, quadratic and multiplicative rules.
  2. Detect interleaved series, where alternate terms follow two separate rules, before concluding a sequence has no pattern.
  3. Convert letter sequences to alphabet positions, apply the same difference machinery, and wrap correctly past position 26.
  4. Explain why a finite sequence is under-determined, and choose between competing rules by testing each against every given term rather than the first two.
  5. Induce a decision rule from a small table of labelled cases, and identify the single row that rules out the obvious over-general hypothesis.
  6. Design the test that could disconfirm your hypothesis, and recognise why confirming cases are worth far less than disconfirming ones.

Worked examples and pitfalls

Differences first, ratios second: Four series, each solved by the same opening move. Series one: 2, 6, 12, 20, 30. First differences are 4, 6, 8, 10: arithmetic, rising by 2, so the next difference is 12 and the next term is 42. The closed form is n times n-plus-one: 1x2, 2x3, 3x4, 4x5, 5x6, 6x7 = 42, which confirms it. Series two: 7, 10, 16, 28, 52. First differences are 3, 6, 12, 24. Those are doubling, so the next difference is 48 and the next term is 100. Equivalently each term is double the previous minus 4: 7x2-4 = 10, 10x2-4 = 16, 16x2-4 = 28, 28x2-4 = 52, 52x2-4 = 100. Series three: 3, 4, 7, 11, 18, 29. Nothing simple in the differences, so try summing neighbours: 3+4 = 7, 4+7 = 11, 7+11 = 18, 11+18 = 29, and the next term is 18+29 = 47. Series four: 1, 4, 9, 61, 52. That looks broken until you notice 61 and 52 are 16 and 25 with their digits reversed; the underlying series is the squares 1, 4, 9, 16, 25, 36, written back-to-front where reversing changes anything, so the next term is 63. The order of attack that solves most series is fixed: first differences, then second differences, then ratios, then sums of neighbours, then digit manipulation. Run it in that order and you stop staring.

Two rules fit; the fourth term decides: You are shown 2, 4, 8 and asked for the next term. Doubling gives 16. But first differences are 2 and 4, and if those differences are themselves rising by 2 the next difference is 6 and the next term is 14. Both rules fit every term you were given, so the sequence is genuinely under-determined and neither answer is more correct than the other from the data alone. This is not a trick; it is the central limitation of induction, and assessment writers manage it by giving you enough terms to separate the candidates. Add one term. If the series is 2, 4, 8, 14 then the differences are 2, 4, 6 and the next difference is 8, giving 22, doubling is dead, because doubling would have produced 16 at position four. If the series is 2, 4, 8, 16 the difference rule is dead instead, because it predicted 14. So the practical rule is: never commit on two terms, always test your candidate rule against the LAST given term as well as the first, and if two rules survive all given terms, look at the answer options, exactly one of them will normally correspond to a rule that fits, and that is legitimate evidence about what the writer intended.

Letters are numbers wearing a costume: The sequence C, F, J, O, U. Convert to alphabet positions: C is 3, F is 6, J is 10, O is 15, U is 21. First differences are 3, 4, 5, 6, rising by one, so the next gap is 7 and the next position is 28. The alphabet has only 26 letters, so wrap: 28 minus 26 is 2, which is B. Answer B. Three things go wrong on letter items. Candidates count gaps by reciting the alphabet on their fingers and drop a letter, which is why writing the numbers down beats counting in your head every time. Candidates forget to wrap, and answer with a position number rather than a letter. And candidates mishandle a series that runs backwards past A. Position 1 minus 3 is minus 2, which wraps to 26 minus 2, that is 24, the letter X. A related family uses letter pairs where the two letters move at different rates, for example AZ, CX, EV, GT: the first letters are 1, 3, 5, 7 going up by two and the second are 26, 24, 22, 20 going down by two, so the next pair is I and R, that is IR. Split the pair, treat each stream separately, and the item becomes two easy arithmetic series instead of one impossible one.

Interleaving: two clocks in one series: The series 5, 8, 6, 11, 7, 14, 8. First differences are 3, minus 2, 5, minus 4, 7, minus 6: alternating sign, no obvious progression, and this is the point where candidates guess. Split it instead. Terms in the odd positions are 5, 6, 7, 8, rising by one. Terms in the even positions are 8, 11, 14, rising by three. The next term sits in an even position, so it continues the second stream: 14 plus 3 is 17. The diagnostic that should trigger the split is alternating signs in the first differences, or a series that oscillates while drifting. Interleaving also appears with three streams, and with one stream constant: 4, 9, 4, 16, 4, 25 hides the squares 9, 16, 25 among repeated 4s, so the next term is 4 and the one after is 36. One caution worth carrying: a series that has been split should be checked back against the original by writing out your predicted term in place and reading the whole thing again. If the reassembled series looks stranger than the one you started with, the split was probably wrong.

Inducing a rule from labelled cases: Five support tickets, each with a customer tier, a first-response time, and whether it was escalated. Ticket 1: Enterprise, 6 hours, escalated. Ticket 2: Enterprise, 2 hours, not escalated. Ticket 3: Standard, 9 hours, not escalated. Ticket 4: Enterprise, 5 hours, escalated. Ticket 5: Standard, 1 hour, not escalated. Three hypotheses are worth writing down. Hypothesis A: escalation happens when the response is slow. Ticket 3 kills it. A nine-hour Standard ticket was not escalated. Hypothesis B: escalation happens for Enterprise customers. Ticket 2 kills it. A fast Enterprise ticket was not escalated. Hypothesis C: escalation requires BOTH Enterprise tier and a response over four hours. It fits all five rows, and it is the only conjunction that does. Notice which rows did the work: the two that fit one hypothesis but not the label are worth more than the three that agree with everything. Now the honest limit. Does an Enterprise ticket answered in exactly four hours escalate? Hypothesis C as written says no, but the data contains no case between two and five hours, so the true threshold could be anywhere in that window. Induction from five rows gives you a rule and a region of ignorance, and naming the region is part of the answer.

Look for the case that would break you: Four cards lie on a table showing A, K, 4 and 7. Each card has a letter on one side and a number on the other. The rule to test: if a card has a vowel on one face, it has an even number on the other. Which cards must you turn? Most people say A, and many add 4. A is right: a vowel with an odd number on the back refutes the rule directly. The 4 is useless: the rule says nothing about what must be behind an even number, so a consonant there breaks nothing and a vowel there merely agrees. The card people miss is the 7. Turn it, find a vowel, and the rule is dead. So the answer is A and 7, the two cards that could produce a violation. This is the Wason selection task, a well-known public result in the psychology of reasoning, and the reason it belongs in an inductive lesson is that it isolates the habit the construct actually rewards: people search for confirming evidence by default and have to be trained to search for disconfirming evidence. Carry it into series items as a check. Once you have a candidate rule, do not run it forward on the terms it was built from; run it on the term you have not used yet, and treat a single mismatch as fatal rather than as noise.

How to practise this skill

  • Write the first differences under every numeric series before you think about it at all. The mechanical step surfaces arithmetic and quadratic rules for free and tells you within seconds whether to move on to ratios.
  • Fix an order of attack and follow it: first differences, second differences, ratios, sums of adjacent terms, then digit tricks. Most lost time in this construct is spent re-staring at a series rather than working through the list.
  • Convert letters to numbers on paper the moment you see a letter series, and write the alphabet with positions at the top of your rough sheet once at the start of a session rather than counting on your fingers per item.
  • Treat alternating signs in the first differences as a direct instruction to split the series into odd and even positions. The interleaved family is large and is where candidates most often decide, wrongly, that there is no pattern.
  • Validate a candidate rule against the last given term, not the first two. A rule that explains the opening of a series and misses its final term is the standard wrong answer, and the answer options are usually built to reward it.
  • When you induce a rule from a table of cases, name the row that eliminated the simpler hypothesis and name the gap the data leaves open. Both are recorded on this device only, so build the habit here where over-claiming is free.

Glossary

Inductive inference
Reasoning from particular observations to a general rule. The conclusion is supported but never guaranteed, which is the essential difference from deduction.
First difference
The gap between consecutive terms of a series. A constant first difference means an arithmetic progression; a constant second difference means a quadratic rule.
Geometric progression
A series where each term is the previous term multiplied by a fixed ratio. Detected by dividing neighbours rather than subtracting them.
Interleaved series
A single printed sequence containing two or more independent series in alternate positions. Signalled by first differences that alternate in sign.
Under-determination
The condition in which several different rules fit every term you were given, so the data alone cannot single one out. It is the reason short series need extra terms or answer options to be decidable.
Disconfirming instance
A case that a hypothesis predicts should not exist. One of these refutes a rule outright, whereas any number of agreeing cases only fails to refute it.
Confirmation bias
The tendency to seek evidence that agrees with a hypothesis already held. In series and rule-induction items it shows up as checking a rule against the terms that suggested it.
Wrap-around
Continuing a letter sequence past Z back to A, or before A back to Z, by adding or subtracting 26 from the alphabet position. The routine source of near-miss answers on letter items.

Where this material comes from

  • Worked series written for Novus Learn from standard sequence analysis: first and second differences, geometric ratios, neighbour sums, alphabet-position arithmetic, and interleaved streams. Every series above was extended and checked term by term.
  • The four-card selection problem is the Wason selection task, first published by P. C. Wason in 1968 and widely reproduced in the public psychology-of-reasoning literature; the description above is a plain restatement of the standard version, not an item from any commercial test.
  • Terminology checked against the public Wikipedia articles 'Inductive reasoning', 'Arithmetic progression', 'Geometric progression' and 'Wason selection task'. Definitions only.
  • Novus Learn aptitude construct registry (catalog seed) for the construct scope and related suite mapping.
  • Public educational framing only: not affiliated with any official exam board, publisher or employer, and no copyrighted test item is reproduced.

Educational preparation only. Novus Learn does not administer official exams and does not guarantee scores or hiring outcomes.

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