How to Learn Advanced English Vocabulary (Chinese Edition) | Lesson No.035 | Master Probability, Likelihood, Possibility, Risk and Uncertainty Without Confusing What Can Happen with What Will Probably Happen | 第035课：掌握概率、可能性、风险与不确定性，避免把“可能发生”写成“很可能发生”

Series ID: EDKS-ADV-VOC-ZH-0035 · Advanced English Vocabulary (Chinese Edition) · Lesson No.035 · C1 → C2 · 简体中文辅助

Possible does not mean probable. Uncertain does not mean equally likely. Risk is not the same as uncertainty.
“可能发生”不等于“很可能发生”；“不确定”不等于“各种结果机会一样”；“风险”也不等于一般的不确定性。

Advanced learners often lose precision when they talk about the future, incomplete evidence or competing outcomes. They know words such as possible, likely, probably, risk, uncertainty, yet treat them as a loose family of “maybe” vocabulary. The result is not a grammar error. It is a reasoning error expressed through vocabulary.

Cambridge defines possibility as a chance that something may happen or be true. It defines probability as the level of possibility of something happening or being true, likelihood as the chance that something will happen, risk as the possibility of something bad happening, and uncertainty as a situation in which something is not known or certain. Those definitions overlap, but the words do not perform identical jobs in real reasoning.

This lesson teaches the lexical architecture behind uncertain outcomes. It asks five questions repeatedly: Can it happen? How likely is it? What evidence supports that judgment? What could be lost if the bad outcome occurs? What remains unknown? When learners answer those questions separately, their English becomes more precise without becoming more complicated.

Possibility opens the door. Probability and likelihood tell us how wide the door is. Risk asks what happens if the bad outcome walks through it. Uncertainty tells us what we still do not know.

possibility 先问“会不会发生”；probability / likelihood 再问“有多大可能”；risk 问“坏结果发生会怎样”；uncertainty 问“我们还不知道什么”。

This lesson owns the Mandarin-supported C1–C2 vocabulary route for probability, likelihood, possibility, chance, odds, uncertainty, certainty, confidence, risk, exposure, prospect, plausibility and decision language under incomplete knowledge. It coordinates but does not replace Lesson No.020 on general hedging and stance, Lesson No.029 on degree and scalar strength, Lesson No.032 on causation, Lesson No.033 on evidence-to-conclusion stages, or Lesson No.034 on conditions and rule boundaries.

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Part I — Build the uncertainty map | 第一部分：先建立“不确定性地图”

1. Possibility asks whether an outcome remains open | possibility = 是否仍有可能

If something is possible, it can happen or be true. That statement does not tell you that it is likely. A one-in-a-million outcome may still be possible. This is the first distinction advanced learners must protect. “It is possible that the flight will be cancelled” keeps cancellation inside the outcome set. “The flight is likely to be cancelled” moves much further: cancellation is now expected or more probable than a merely open possibility.

2. Possible is often a gate, not a percentage | possible 先开门，不一定量化

Possible often answers a binary conceptual question: Is this outcome still compatible with what we know? It does not automatically assign a numerical probability. In academic and professional writing, “X is possible” may be intentionally weak because the evidence supports only non-exclusion. Do not upgrade it to “X is likely” unless evidence justifies a higher likelihood judgment.

3. Possibility can also mean an option | possibility has an option sense

Cambridge also uses possibility for something you can choose to do: “Hiring temporary staff is one possibility.” This is not probability language at all. It means option. Learners should therefore separate two senses: epistemic possibility—something may happen or be true—and practical possibility—something is an available course of action.

4. Probability asks how likely an outcome is | probability = 发生可能性的程度

Probability can be general English or a formal mathematical quantity. In general English, it refers to how likely something is. In mathematics and statistics, probability can be represented numerically under a defined model. Do not slide carelessly between these senses. “There is a high probability of delay” is an ordinary likelihood statement. “The estimated probability is 0.72” is a quantified analytical statement that requires a method or model.

5. Probability is not a synonym for possibility in every sentence | probability ≠ possibility

Compare: “There is a possibility of system failure” and “There is a high probability of system failure.” The first says failure remains possible. The second says failure is comparatively likely. Replacing possibility with probability changes commitment. This is why a thesaurus cannot make the decision for you.

6. Likelihood is close to probability but often feels less mathematical | likelihood = 发生机会/可能性高低

Oxford and Cambridge both connect likelihood with chance/probability. In ordinary academic and professional prose, likelihood often works naturally when comparing outcomes: increase the likelihood of X, reduce the likelihood that Y, little likelihood of Z. In statistics, however, likelihood can also have a specialised technical meaning distinct from probability. If you work in that field, follow the formal definition.

7. Probability and likelihood share territory but not every technical meaning | technical boundary

For general English learners, “probability” and “likelihood” can often describe how likely an event is. For advanced technical learners, they should not assume mathematical interchangeability. This is a recurring Lesson No.019 principle: a familiar general word can acquire a narrower domain-specific meaning. Mark the domain when the distinction matters.

8. Chance is broad, common and often conversational | chance = 常用的“机会/可能性”

Chance is highly versatile: a good chance, little chance, chance of success, by chance, take a chance. “There is a good chance she will agree” is natural everyday English. In formal technical writing, probability or likelihood may be more precise. Do not assume formal always means better; the correct register depends on audience and purpose.

9. Chance has a second meaning: opportunity | chance ≠ only probability

“I had a chance to speak” means an opportunity, not a probability. “There is a chance I will speak” means the event may occur. This polysemy is easy for advanced learners to overlook because Chinese often uses 机会 for opportunity but 可能 for uncertain outcome. English uses chance for both.

10. Odds express likelihood and can also belong to betting | odds = 发生几率/赔率

Cambridge and Oxford define odds as the degree/probability that something will happen; the word also has a betting sense. Common general phrases include the odds are that…, odds of success, odds against, against the odds. “The odds are against us” means success is unlikely under current conditions. Because odds may be technical or idiomatic, do not treat every use as a direct percentage statement.

11. Prospect is possibility viewed from the future | prospect = 未来可能性/前景

A prospect is often a future possibility, especially one imagined as approaching: the prospect of recovery, little prospect of success, future prospects. It can carry emotional or evaluative colouring depending on what the future event is. “The prospect of delay” is not simply a probability statement; it presents delay as a contemplated future outcome.

12. Plausibility asks whether an explanation is believable | plausible ≠ probable

An explanation can be plausible because it is reasonable and consistent with what we know, yet still not be the most probable explanation. Plausibility is about credibility or fit with knowledge; probability is about likelihood. In research discussion, “a plausible explanation” should not silently become “the likely explanation” without comparative evidence.

13. Conceivable is weaker and more imagination-based | conceivable = 可以想象得到

If an outcome is conceivable, we can imagine it as possible. This can be much weaker than likely. “It is conceivable that demand could double” does not say doubling is expected. The word is useful when exploring scenario space, but weak evidence should not be mistaken for high probability.

14. Feasible is about practical possibility | feasible = 实际上做得到

Feasible answers whether a plan can realistically be done with available technology, resources or conditions. A plan can be feasible but unlikely to be approved. It can also be likely to be approved but technically infeasible. This contrast is extremely useful: possible/probable describe outcome status; feasible describes practical achievability.

15. Viable adds sustainability or ability to work successfully | viable = 能持续运作/可行

A proposal may be technically feasible but not commercially viable. A biological organism may be viable in a different technical sense. In planning, viable often means capable of working successfully over the relevant period. It should not be used as a synonym for “likely to happen”.

16. Likely is an expectation word | likely = 预期会发生

Cambridge explains likely as expected or probably going to happen. Common frames include be likely to + verb, it is likely that…, likely outcome, more/less likely. The word moves beyond bare possibility. It tells the reader that the outcome has meaningful probability or expectation relative to alternatives.

17. “Likely” has no universal percentage | likely ≠ fixed 70%

Do not teach learners that likely always equals a fixed percentage such as 70%. Natural-language probability words are context-sensitive. Different speakers, domains and tasks may use them differently. If a number matters, give the number. If the source uses only a verbal term, preserve the verbal level rather than inventing precision.

18. Probable is close to likely but distribution differs | probable = 很有可能/较大概率

Probable often appears in more formal or analytical contexts: probable cause, probable outcome, probable explanation, highly probable. In ordinary conversation, likely is often more natural. “She is probable to arrive” is not normal English; use “She is likely to arrive” or “It is probable that she will arrive.” Learn the grammar frame with the meaning.

19. Possibly, probably and likely occupy different grammar slots | grammar supports meaning

Possibly and probably are adverbs: “It will probably rain.” Likely is commonly an adjective in international learner English: “It is likely to rain.” Some varieties, especially American English, also use adverbial likely: “It will likely rain.” C1–C2 learners should notice both grammar and register rather than treating probability vocabulary as interchangeable tokens.

20. Maybe and perhaps are broad everyday uncertainty markers | maybe / perhaps

Maybe and perhaps mark possibility without specifying a precise probability. Maybe is common in conversation; perhaps can sound slightly more neutral or formal depending on context. Neither automatically means 50%. “Maybe he will come” simply keeps the outcome open.

21. Perhaps can soften a suggestion as well as mark uncertainty | pragmatic function

“Perhaps we should revise the plan” may not express serious uncertainty about whether revision is good. It can soften interpersonal force. This is where Lesson No.020 and Lesson No.035 meet: the same lexical item can encode epistemic uncertainty and interpersonal politeness. Determine the communicative job from context.

22. Potential marks unrealised capacity or possible development | potential = 潜在的

Potential often describes something that could develop or become actual: potential problem, potential benefit, potential customer, potential explanation. It does not say the event is likely. A potential hazard can be very unlikely but still worth considering because consequences are severe. This becomes important when we move from probability to risk.

23. Potentially is not the same as probably | potentially ≠ probably

“This change could potentially save millions” means the saving is possible under some conditions. “This change will probably save millions” says the saving is expected. Confusing the two inflates evidence. Advanced writers should be especially careful because potentially often appears in promotional or speculative language.

24. Uncertainty names what is not known or not certain | uncertainty = 未知与不确定状态

Cambridge defines uncertainty broadly as a situation in which something is not known or certain. That means uncertainty is not itself a probability value. We may know that the probability of rain is 60% while still being uncertain about the outcome. Or we may be uncertain about the probability itself because the model is poor. These are different layers.

25. Outcome uncertainty and probability uncertainty are different | 两层不确定性

Suppose a reliable model says there is a 60% chance of rain. The outcome is uncertain: rain may or may not occur. But the probability estimate may be relatively well supported. Now suppose data are sparse and estimates range from 30% to 80%. We are uncertain both about the outcome and about the probability estimate. Advanced English should be able to name both situations.

26. Unknown is not the same as unlikely | unknown ≠ low probability

If we do not know the probability of an event, we cannot automatically call it unlikely. “The likelihood is unknown” is not “the likelihood is low.” This error appears frequently when people treat lack of evidence as evidence of rarity. Vocabulary can protect reasoning: use unknown, uncertain, insufficiently estimated when the problem is missing knowledge.

27. Indeterminate means not yet determinable from available information | indeterminate = 尚不能确定

Indeterminate is more formal and often technical. A test result can be indeterminate; a cause can remain indeterminate; a classification may be indeterminate. It does not mean “probably negative” or “probably positive”. It means the available information does not support a determinate answer.

28. Ambiguous is not uncertainty about probability | ambiguity ≠ uncertainty

An ambiguous statement or signal supports more than one interpretation. Uncertainty is broader: we may know what the question means but not know the answer. “The instruction is ambiguous” means the wording permits multiple readings. “The outcome is uncertain” means the future/result is not known. Do not use the terms as synonyms.

29. Doubt is a stance toward truth, not a probability measure | doubt = 怀疑

“I doubt that X” expresses the speaker’s lack of belief or expectation. It is stronger and more personal than simply saying “X is uncertain.” “There is doubt about X” can be more impersonal. Neither gives a numerical probability unless further specified. Lesson No.020 handles the stance dimension; Lesson No.035 asks what probability judgment sits behind it.

30. Certainty is the opposite pole, but absolute certainty is rare | certainty = 确定性

Oxford defines certainty as the state of being certain. Useful phrases include with certainty, degree of certainty, near certainty, virtual certainty, no certainty that…. In evidence-based writing, absolute certainty is often stronger than the evidence permits. But learners should not hedge facts that are genuinely established. The goal is calibration, not permanent caution.

31. Certain can describe belief or expected outcome | two common jobs

“I am certain that the file was saved” describes the speaker’s confidence. “The machine is certain to fail under these conditions” predicts an outcome as virtually unavoidable. These senses are related but not identical. In the first, certainty belongs to the knower; in the second, it is attached to the expected event.

32. Confidence belongs to the judge, estimate or procedure | confidence ≠ probability of event

“I am confident that the plan will work” reports a judgment state. It does not by itself provide the probability that the plan works. “High confidence” can also be technical in statistics or machine learning, where definitions vary. Do not convert confidence directly into event probability unless the model or field explicitly defines the relationship.

33. Confident and certain are not identical | confidence can be psychological

A person can be highly confident and wrong. Confidence describes strength of belief, assurance or model output; certainty describes absence or near absence of doubt in ordinary language. Neither guarantees truth. Evidence quality must remain separate from how strongly someone feels.

34. Risk narrows uncertainty toward bad outcomes | risk = 坏结果发生的可能性

Cambridge’s core general-English definition is useful: risk is the possibility of something bad happening. This negative-outcome orientation distinguishes risk from neutral uncertainty. We can be uncertain whether a coin lands heads or tails without calling either outcome a “risk” in ordinary language. We call something a risk when harm, loss, failure or another undesirable result matters.

35. Risk may include probability and consequence in technical frameworks | domain caution

Many technical risk frameworks evaluate both how likely an adverse event is and how severe its consequences would be. But definitions and formulas vary by field. Do not teach one universal equation as if all domains define risk identically. In general English, the safe owner is: risk concerns the possibility of harm or loss; technical learners then adopt their field’s formal model.

36. High risk is not always high probability | severity can matter

A rare event can still be treated as a serious risk if its consequences are catastrophic. Conversely, a common minor inconvenience may have high probability but low practical risk. This is why “high risk” should not automatically be paraphrased as “very likely”. Ask whether the domain’s judgment includes consequence severity as well as likelihood.

37. Risk of, risk to and at risk encode different structures | grammar network

Risk of X names the adverse event: “risk of failure”. Risk to Y names what may be harmed: “risk to public health”. At risk of X describes an exposed entity: “The server is at risk of overheating.” Put X at risk means create or increase danger. Store the preposition with the relation.

38. Risk factor is not the same as cause | risk factor ≠ proven cause

A risk factor is associated with increased risk in the relevant domain; it does not automatically establish a complete causal mechanism. Lesson No.032’s boundary remains essential. If an article calls X a risk factor, do not paraphrase “X causes Y” unless causation is separately established.

39. Exposure names contact with a hazard or uncertain influence | exposure

In health, finance, cybersecurity and environmental contexts, exposure can describe the extent to which a person, organisation or asset is subject to a hazard or source of risk. The exact technical meaning varies. Exposure is not probability. A system can have high exposure to a hazard while the probability of loss depends on additional controls and conditions.

40. Hazard is a source of potential harm | hazard ≠ risk

A hazard is commonly understood as something with potential to cause harm; risk concerns the possibility/likelihood and consequences of harm under exposure. The precise distinction varies by technical framework, but learners should avoid using the words as automatic synonyms. A chemical may be hazardous even when controls keep actual risk low.

41. Vulnerability is susceptibility, not probability | vulnerability

Vulnerability describes weakness or susceptibility to harm. A vulnerable system may be exposed to a hazard, but a particular incident may still be unlikely. In cybersecurity, public health and social policy, definitions can become technical. The transferable distinction is: vulnerability describes how susceptible something is; probability describes how likely an event is.

42. Threat is a potential source/event of harm | threat

A threat can be a person, event or condition capable of causing harm. It does not automatically tell us probability. “A credible threat” may be taken seriously even when likelihood remains uncertain. In security domains, threat, vulnerability, exposure and risk may have formal relationships; follow the relevant framework rather than ordinary intuition.

43. Opportunity risk and upside uncertainty need separate language | uncertainty can be positive

General uncertainty includes good, bad and neutral outcomes. Some professional fields talk about upside risk or opportunity, but ordinary English often associates risk with adverse outcomes. When the outcome may be beneficial, words such as opportunity, upside, potential gain, possibility may be clearer unless the field deliberately uses symmetric risk terminology.

44. The first uncertainty map | 第一张不确定性地图

Question	Useful vocabulary	Do not confuse with
Can it happen?	possible, possibility, conceivable	likely/probable
How likely?	probability, likelihood, chance, odds	mere possibility
Is the explanation reasonable?	plausible	most probable
Can the plan work?	feasible, viable	likely to be approved
What is not known?	uncertainty, unknown, indeterminate	unlikely
How sure is the judge?	certainty, confidence	event probability
What bad outcome matters?	risk, hazard, threat, exposure	neutral uncertainty

45. Part I checkpoint | 第一部分检查点

At this point, the learner should be able to explain one crucial chain: possible → likelihood/probability → evidence → uncertainty → risk → decision. The arrows do not mean every step is numerical. They mean each word answers a different question. If you can preserve those questions, advanced probability vocabulary becomes a reasoning system rather than a list of synonyms.

Part II — Grade probability without inventing precision | 第二部分：给可能性分级，但不要制造虚假精度

46. Natural-language probability is graded, not exact | 自然语言概率不是固定百分比

Words such as possible, plausible, likely, probable, unlikely, almost certain form a rough probability landscape, but not a universal numeric scale. Different speakers may assign different internal thresholds. Different fields may define verbal categories formally, while ordinary conversation remains flexible. The safest rule is: do not invent a percentage for a verbal term unless the source or domain defines one.

47. “Possible” sits below “likely” in commitment | possible vs likely

“It is possible that the server will fail” keeps failure open. “It is likely that the server will fail” says failure is expected or comparatively probable. If the evidence merely shows that failure cannot be ruled out, possible may be correct. If repeated observations make failure the expected outcome, likely may be justified. The lexical choice should track evidence, not drama.

48. “Plausible” belongs to explanations as much as events | plausible explanation

A plausible explanation fits known facts and is reasonable enough to consider. It may compete with several other plausible explanations. This makes plausible especially useful in research discussion, diagnosis and problem solving. Do not convert “plausible” into “probable” unless comparative evidence ranks the explanation above alternatives.

49. “Likely” often predicts an outcome | likely outcome

Common patterns include the likely outcome, the most likely explanation, likely to increase, likely to remain. Notice that most likely is comparative: it can be the leading option even when absolute probability is not high. If three outcomes have probabilities 40%, 35% and 25%, the 40% outcome is the most likely while still being less likely than not to occur. This is a subtle but important distinction.

50. “Most likely” does not mean “almost certain” | ranking vs absolute likelihood

“Most likely” compares options. “Almost certain” describes a very high absolute degree of expectation. A learner may read “X is the most likely explanation” and paraphrase “X is almost certainly correct.” That is unsafe. The first only says X ranks above alternatives. The second says doubt is minimal.

51. “Probable” can sound more analytical or formal | probable outcome

Probable often appears before nouns or in impersonal clauses: probable outcome, probable cause, it is probable that…. The exact distribution varies by variety and genre. For many learners, likely is more flexible in everyday English because it works naturally with infinitives: “The team is likely to win.” Learn the syntax as part of lexical control.

52. “Unlikely” means low expectation, not impossibility | unlikely ≠ impossible

If an outcome is unlikely, it can still happen. “A major failure is unlikely” should never be paraphrased “A major failure cannot happen.” This difference matters in safety, policy, medicine, finance and ordinary planning. Low probability and zero possibility are different categories.

53. “Highly unlikely” is still not “impossible” | stronger low-probability language

Highly unlikely pushes the outcome further down the probability scale, but it still normally leaves the possibility open. If the event is logically or physically impossible, say impossible. If the event is merely very rare, preserve rarity rather than converting it into impossibility.

54. “Impossible” closes the possibility set | impossible = 不可能

Impossible is an absolute word in its core sense. It says the event cannot occur or the action cannot be done. In informal speech people exaggerate—“It’s impossible to find parking”—but in technical or academic writing, the word should be reserved for genuinely excluded outcomes or clearly defined constraints.

55. “Almost impossible” reopens a tiny possibility | almost impossible

Almost impossible is rhetorically strong but logically different from impossible. It says the event is extraordinarily difficult or unlikely, not strictly excluded. In technical contexts, a more measurable description may be better: extremely unlikely, below the detection capability, outside feasible operating limits.

56. “Almost certain” is very strong but still preserves a small residual doubt | near certainty

Cambridge gives examples such as almost certain and virtually certain. These are near-certainty expressions. They should not be used simply because the writer personally expects an outcome. The evidence or domain convention must justify very high confidence.

57. “Virtually certain” is not literally certain | virtually certain

Virtually certain means so likely that for practical purposes the remaining uncertainty is very small. The word virtually protects the statement from absolute certainty. Removing it strengthens the claim. That single adverb can therefore carry important epistemic work.

58. “Expected” can describe forecast, norm or obligation | expected is polysemous

“Sales are expected to rise” expresses forecast. “Students are expected to submit on time” may express a norm or obligation. “The expected value” has a technical mathematical meaning. Do not assume expected always equals “likely”. Grammar and domain decide which sense is active.

59. Forecast language carries model/source responsibility | forecast / projection / prediction

A forecast, projection or prediction can be associated with a model, expert or assumption set. These nouns describe outputs or acts of predicting, not probability levels by themselves. A forecast can be uncertain; a projection may be conditional on assumptions; a prediction may be probabilistic or deterministic. Keep the uncertainty architecture attached to the forecasting noun.

60. “May” often marks possibility | may = 可能

Academic Phrasebank uses may extensively to express cautious possibility: “This inconsistency may be due to…” The modal is useful precisely because it does not overstate certainty. But may also expresses permission: “You may leave.” Context distinguishes epistemic possibility from deontic permission.

61. “Might” often feels more tentative, but no fixed percentage exists | might

In many contexts, might sounds more tentative than may, especially in hypothetical or cautious reasoning. But natural usage varies and neither word maps to a universal probability. Do not build a fake numeric ladder such as might = 30%, may = 50%. Teach discourse force and examples instead.

62. “Could” can mark possibility, ability or conditional consequence | could has multiple jobs

“The discrepancy could reflect measurement error” marks one possible explanation. “She could swim at five” marks past ability. “If demand rose, prices could increase” marks conditional possibility. Because could is so flexible, learners should reconstruct the relation before translating it.

63. “Must” can express strong inference, not only obligation | epistemic must

“The lights are off; they must have left” expresses a strong inference. This is different from “Employees must wear badges,” which imposes obligation. Epistemic must places the speaker near the high-certainty end based on evidence. It does not mean logical proof in every context.

64. “Can’t” can express strong negative inference | epistemic can’t

“That can’t be correct” often means the speaker considers the proposition impossible or extremely implausible given current evidence. It may be stronger than “That is unlikely to be correct.” Again, the modal has other senses—ability and permission—so context matters.

65. “Should” can express expectation | should as probability/expectation

“The train should arrive by six” usually expresses reasonable expectation, not obligation. “You should submit the form” expresses advice. This distinction is critical in spoken and written professional English. A forecast with should is usually less absolute than will.

66. “Will” can predict, promise or state scheduled consequence | will is not always certainty

“The system will restart automatically” may describe programmed behaviour. “It will rain tomorrow” is a prediction. “I will send it” can be a commitment. Do not treat every will as a calibrated probability statement. The verb participates in future reference, volition and prediction.

67. “Probably” is stronger than “possibly” | probably vs possibly

“It will possibly fail” says failure is one open outcome. “It will probably fail” says failure is expected. Because these adverbs can occupy similar positions in a sentence, learners sometimes treat them as stylistic alternatives. They are not. The difference is epistemic strength.

68. “Presumably” signals an inference from what is assumed or known | presumably

Presumably often means “I suppose this is the case because available facts make it reasonable.” It carries an inferential flavour. “The office is closed, so presumably the staff have gone home.” This is not a direct probability estimate; it exposes the reasoning stance of the speaker.

69. “Apparently” reports appearance or second-hand information | apparently

Apparently can signal that something seems true from available evidence or reports. It often distances the speaker from full commitment. “Apparently, the launch has been delayed.” The source may be indirect. Do not use apparently as a synonym for “probably”; it carries source/evidence implications.

70. “Seemingly” foregrounds appearance, sometimes with later reversal | seemingly

“A seemingly simple problem” describes how something appears, often leaving open the possibility that reality differs. This word belongs more to appearance/interpretation than pure probability. It can signal caution, irony or later complication.

71. “Arguably” means a defensible case can be made | arguably ≠ probably

Arguably says a proposition can reasonably be argued, not that it has a particular probability of being true. “This is arguably the strongest section” signals evaluative defensibility. It belongs to stance and argumentation, not event likelihood. Learners who translate every hedge as “maybe” miss this distinction.

72. “Potentially” marks possible consequence, often without probability | potentially

“The error is potentially serious” means seriousness could become relevant under some conditions. It does not necessarily mean serious consequences are likely. In risk communication, potentially catastrophic can coexist with very low probability. Separate severity language from likelihood language.

73. “Potential” plus a noun often creates a candidate category | potential cause / risk / solution

A potential cause is a candidate cause, not a proven cause. A potential solution is an option worth evaluating, not a guaranteed solution. A potential risk can be redundant or domain-specific because risk already involves possible harm. Evaluate the noun phrase rather than assuming “potential” always improves caution.

74. “There is a possibility that…” is weaker than “the likelihood is that…” | clause frames

These two noun-clause frames look structurally similar but carry different strength. “There is a possibility that demand will fall” opens one outcome. “The likelihood is that demand will fall” presents decline as expected. Sentence frames therefore encode probability even before adjectives are added.

75. “There is every likelihood that…” is very strong | every likelihood

Cambridge and Oxford use every likelihood for a very high expectation. It is idiomatic, not literal arithmetic. Learners should store the phrase as a chunk. Do not reconstruct it as “every probability”.

76. “In all likelihood” means very probably | in all likelihood

In all likelihood is a C2-style phrase meaning very probably/almost certainly in many contexts. It often appears sentence-initially: “In all likelihood, the delay will continue.” Use it when the register supports it; probably is often clearer in ordinary communication.

77. “In all probability” is similarly strong and formal | in all probability

Cambridge marks in all probability as meaning very likely. The phrase is formal and should not be used simply to sound sophisticated. Compare “In all probability, the project will be delayed” with the plainer “The project will probably be delayed.” Same broad commitment, different register.

78. “There is a good chance…” is accessible probability language | good chance

A good chance means an outcome is reasonably likely. It is less technical than high probability. In parent communication, classroom talk or ordinary professional discussion, this may be the better phrase. Register control is part of advanced vocabulary.

79. “Slim chance” means low but non-zero possibility | slim chance

A slim chance is small, not absent. This phrase is useful precisely because it distinguishes low probability from impossibility. “There is only a slim chance of recovery” is stronger than “Recovery is impossible.” The latter closes the outcome entirely.

80. “Fifty-fifty” is informal equality language | fifty-fifty

“It’s fifty-fifty” informally suggests roughly equal chances between two outcomes. Do not use it when there are more than two outcomes or when no basis exists for equal probability. “We don’t know” does not imply fifty-fifty. This is one of the most important uncertainty mistakes to eliminate.

81. Ignorance is not a uniform distribution | 不知道 ≠ 各种结果同概率

If you have no evidence about two outcomes, assigning 50% to each may be unjustified. Natural language should reflect ignorance: “The relative likelihood is unknown,” “We do not yet have enough information to estimate the probability,” or “Both outcomes remain possible, but their probabilities are uncertain.” This is clearer than pretending uncertainty itself supplies numbers.

82. “Even chance” belongs to equal-likelihood situations | even chance

An even chance means roughly equal chances between alternatives. Like fifty-fifty, it requires some reason to believe the alternatives are balanced. If evidence is absent, unknown is often the more honest word.

83. “Odds-on” and betting-derived language can be idiomatic | betting register

Phrases such as odds-on favourite come from betting and may be used figuratively. They can sound journalistic or conversational rather than academic. A learner should recognise them but avoid importing gambling-style odds language into a formal report unless the context supports it.

84. Probability scales need labels plus anchors | verbal scale design

If a team uses a verbal scale—rare, unlikely, possible, likely, almost certain—it should define the categories internally if decisions depend on them. Different organisations may use different numeric anchors. This is a systems lesson: verbal labels become safer when everyone shares the same operational definition.

85. Do not import another institution’s probability vocabulary blindly | local definitions matter

A risk matrix, intelligence report, weather service or medical guideline may define verbal probabilities in its own way. The phrase likely can therefore carry a formal range in one framework and ordinary-language meaning in another. Always check the source’s definitions before comparing statements across systems.

86. Comparative probability is often safer than absolute labels | more likely / less likely

Sometimes the evidence supports ranking but not a confident absolute estimate. “X is more likely than Y” may be justified even when neither probability is known precisely. Comparative language can therefore be more honest than forcing each outcome into “low/medium/high” categories.

87. “Twice as likely” needs a measurable basis | relative likelihood

“Twice as likely” is quantitative language. It should come from data or a defined model. Do not use it rhetorically to mean “much more likely.” And remember that relative increases can sound dramatic even when absolute probabilities remain small. If the baseline matters, report it.

88. Absolute and relative probability can tell different stories | absolute vs relative

If an event probability rises from 1% to 2%, it has doubled relatively but increased by only one percentage point absolutely. These are both true descriptions. Advanced language should not choose the more dramatic framing without reason. State the baseline when it affects interpretation.

89. “Percentage point” and “percent” are not identical | precision language

An increase from 20% to 30% is an increase of 10 percentage points, or 50% relative to the original 20%. This distinction belongs to quantitative literacy as much as vocabulary. Confusing the terms can make probability changes sound smaller or larger than they are.

90. Part II checkpoint: grade, compare, but do not fabricate | 第二部分检查点

Your verbal probability vocabulary should now support three moves: grade an outcome (possible → likely → almost certain), compare outcomes (more/less/most likely), and refuse false precision when evidence does not justify a number. Natural-language probability becomes advanced when it is calibrated to the evidence and transparent about what remains unknown.

Part III — Separate outcome uncertainty from evidence uncertainty | 第三部分：把“结果不确定”与“证据不确定”分开

91. An uncertain outcome can still have a well-estimated probability | 结果不确定，不代表估计也差

A fair coin toss is uncertain before it lands, but under the usual idealised model the probability of heads is well defined. The event outcome is unknown; the probability model is not necessarily vague. This distinction matters because learners often say “we are uncertain, so the probability is uncertain.” Sometimes that is true. Sometimes only the outcome is uncertain.

92. An estimated probability can itself be uncertain | estimate uncertainty

If a small dataset suggests a 60% failure probability, the estimate may have substantial uncertainty. The right language may be: “The estimated probability is around 60%, but the estimate is imprecise.” This is better than presenting 60% as if it were an exact property of the world.

93. Estimate is a key uncertainty word | estimate = 估计值

An estimate is a value obtained from data, judgment or calculation rather than known with perfect certainty. Useful frames include estimate the probability, estimated likelihood, point estimate, rough estimate, best estimate. The noun reminds readers that the value has been inferred rather than directly known.

94. Approximate is not inaccurate by definition | approximate

Approximate means close rather than exact. An approximate probability may be entirely appropriate when data or decisions do not justify more precision. “About 30%” can be more honest than “29.74%” if the underlying evidence is weak. Precision in digits should not exceed precision in knowledge.

95. Precise and accurate are different | precision ≠ accuracy

Precision concerns exactness or spread; accuracy concerns closeness to the true or correct value. A model can output a very precise-looking number and still be systematically wrong. Conversely, an approximate range may be more accurate than a falsely precise point value. Advanced probability language should keep these concepts separate.

96. A confidence interval is not “the probability the true value is inside” in every framework | technical caution

Confidence interval is a technical statistical term whose interpretation depends on the statistical framework and procedure. Learners should not improvise intuitive definitions. In general explanatory English, it is safer to say the interval expresses uncertainty around an estimate, then follow the field’s formal definition when technical accuracy is required.

97. Confidence level is not personal confidence | statistical vs ordinary confidence

A statistical confidence level is a property of a procedure under defined assumptions, not simply how confident a researcher feels. Ordinary “I am 95% confident” may sound similar but is conceptually different. Domain labels matter: statistical confidence, subjective confidence, model confidence can each mean different things.

98. Uncertainty range can be clearer for general readers | uncertainty range

When communicating to non-specialists, phrases such as estimated range or uncertainty range may be easier to understand than specialised statistical terms, provided they accurately reflect the method. The goal is not to replace technical definitions but to translate them without changing what the numbers mean.

99. Error has several meanings and should be specified | error ≠ mistake only

In everyday English, an error is a mistake. In measurement and statistics, error may describe deviation, residual variation or sampling error without implying human incompetence. A learner should ask what kind of error is being named: measurement error, sampling error, model error, clerical error. The modifier changes interpretation.

100. Sampling error does not mean the sampling was done wrongly | sampling error

Sampling error refers to variation arising because a sample rather than the entire population is observed. This is not the same as a mistake in choosing participants. Use sampling bias or another term when the design systematically misrepresents the population. Again, technical vocabulary separates uncertainty source from procedural failure.

101. Measurement uncertainty concerns how well a quantity is known | measurement uncertainty

No real measurement is perfectly exact. Measurement uncertainty expresses limited knowledge about the measured quantity under a measurement procedure. In general writing, the phrase is useful when the uncertainty comes from instruments, calibration, resolution, environmental variation or method—not from future randomness.

102. Variability is not the same as uncertainty | variability ≠ uncertainty

Variability describes how much observed values differ from one another. Uncertainty describes limited knowledge. A process can be highly variable but well characterised, or relatively stable but poorly measured. When learners say “there is a lot of uncertainty because the values vary,” they should ask whether the issue is natural variation, measurement, or both.

103. Variation can be real rather than error | variation

Students, markets, biological organisms and machines can genuinely vary. Treating all variation as noise or error can be conceptually wrong. Advanced language distinguishes natural variation, measurement noise, random error, systematic bias, between-group variation when the domain supports those terms.

104. Noise is unwanted variation or signal disturbance | noise

Noise can be acoustic, statistical, electronic or metaphorical. It often means variation that obscures the signal of interest. Noise increases difficulty of estimation but is not identical to uncertainty itself. A model may quantify noise well; uncertainty can remain about structure or future conditions.

105. Bias is systematic distortion, not just personal prejudice | bias has technical senses

In research and estimation, bias can mean systematic deviation introduced by measurement, sampling, modelling or procedure. This is different from ordinary social prejudice, though the word also has that sense. Probability judgments may be uncertain because of variance, or systematically wrong because of bias. The distinction matters.

106. Uncertainty can arise from missing data | missing information

When crucial observations are absent, use precise language: data are incomplete, information is missing, the estimate is uncertain due to sparse observations. Do not call the outcome “unlikely” simply because evidence is unavailable. Missingness describes knowledge state, not event frequency.

107. Uncertainty can arise from model choice | model uncertainty

Different reasonable models may produce different estimates. This is model uncertainty in broad terms. If a forecast ranges widely depending on assumptions, report that dependency. “The probability is 30%” may be misleading when plausible models produce estimates from 15% to 50%.

108. Assumption uncertainty belongs to the model’s conditions | assumption uncertainty

Lesson No.034 taught assumptions and conditions. Here the question becomes: how much does the probability estimate depend on assumptions that may be wrong? “The forecast assumes stable demand; if demand changes, the estimated likelihood of shortage will also change.” This makes uncertainty traceable rather than vague.

109. Scenario uncertainty asks which future world unfolds | scenario uncertainty

Sometimes uncertainty comes not from poor measurement but from different future pathways: regulation changes, demand rises, technology improves, a competitor enters. Scenario language—under Scenario A, in the high-demand case, under the baseline assumption—can be more honest than pretending one probability summarises every pathway.

110. Structural uncertainty concerns whether the model itself is right | structural uncertainty

A model may include the wrong relationships or omit important variables. This is deeper than parameter uncertainty. Advanced learners need not master every technical taxonomy, but they should recognise the linguistic move: “Uncertainty remains about whether the model structure captures the relevant mechanism.” That is different from saying “the parameter estimate is imprecise.”

111. Aleatory and epistemic uncertainty are specialist terms | technical vocabulary

Some risk and engineering fields distinguish aleatory uncertainty (irreducible/random variability) from epistemic uncertainty (limited knowledge that may be reduced with more information). These are specialist terms, not necessary for every learner. The general conceptual contrast, however, is useful: some uncertainty comes from variability in the world; some comes from what we do not know.

112. More data can reduce some uncertainty but not all | reducible vs irreducible

If uncertainty comes from a small sample, more observations may narrow the estimate. If uncertainty comes from genuinely random future events, more historical data may improve modelling without making the future deterministic. Do not write “more data will eliminate uncertainty.” It may reduce some uncertainty while leaving other sources intact.

113. “Cannot be ruled out” is a non-exclusion phrase | cannot rule out

Academic Phrasebank includes cannot be ruled out as cautious language. The phrase means the possibility remains open. It does not mean the explanation is likely. “Measurement error cannot be ruled out” should not be paraphrased “Measurement error probably caused the result.”

114. “Evidence is insufficient to exclude X” is similar but more explicit | insufficient evidence

This frame locates the uncertainty in evidence rather than the event itself. It says the data cannot eliminate X. The source of uncertainty is visible. Advanced writing improves when the sentence tells readers why uncertainty remains.

115. “Consistent with” does not mean “proves” | evidence compatibility

Results may be consistent with an explanation while also being consistent with alternatives. This language is valuable under uncertainty because it preserves compatibility without overstating uniqueness. Lesson No.033 owns evidence-to-claim stages; Lesson No.035 adds the uncertainty interpretation: compatible evidence may leave several hypotheses open.

116. “Supports” increases credibility but may not determine probability | support

Evidence can support a claim without making it certain. The amount of support depends on evidence quality, alternatives and prior knowledge. “The data support X” should not be automatically translated into “X is highly probable” unless the analytical context justifies that strength.

117. “Suggests” signals a lower-commitment inference | suggests

“The findings suggest that…” is common academic language because it allows an inference without claiming demonstration. The word often signals uncertainty around interpretation. But suggest is not a fixed probability label. It marks discourse stance and evidence strength rather than a universal numeric range.

118. “Indicates” can be stronger, but context decides | indicates

Indicates often sounds more evidentially direct than suggests, but the exact force depends on genre and evidence. Avoid teaching a rigid ladder where suggest = 40% and indicate = 70%. Instead, compare real sentences and ask what claim strength the writer appears to take on.

119. “Evidence of absence” differs from “absence of evidence” | critical uncertainty distinction

Finding no evidence for an effect is not automatically evidence that the effect is absent. Sometimes the study is too weak to detect it. Sometimes strong testing makes absence more plausible. The language should distinguish no evidence was found from evidence indicates no meaningful effect.

120. Base rate is the background frequency | base rate

A base rate is the underlying frequency of an event in a relevant population or context. Probability judgments can become distorted when people focus on a vivid new signal but ignore how common the event was beforehand. The technical mathematics may be complex; the lexical insight is simple: background probability matters.

121. Prior probability is a technical term with framework-specific meaning | prior probability

In Bayesian statistics, prior probability has a formal meaning. In general reasoning, learners may loosely talk about prior expectations. Do not use the technical phrase unless the statistical framework is appropriate. Use initial expectation, background rate, previous estimate when you only mean an earlier belief.

122. Posterior probability is also technical | posterior probability

In Bayesian analysis, posterior probability follows updating with evidence under a defined model. This is not simply “the final probability after thinking.” Advanced learners should recognise the term but avoid casual use outside the statistical context.

123. Update is a useful general verb for changing probability judgments | update beliefs

Even outside formal Bayesian analysis, update is a useful reasoning verb: “New evidence should update our estimate of the likelihood.” This phrase does not require a particular statistical framework. It simply says the probability judgment should change when information changes.

124. Reassess means evaluate the probability again | reassess risk / likelihood

“Reassess the risk after receiving the inspection report.” “Reassess the likelihood once the new data arrive.” These frames connect uncertainty to process. Advanced vocabulary should help learners not only describe uncertainty but manage it over time.

125. Calibrate means align confidence/probability with reality | calibration

In forecasting and probabilistic modelling, calibration can have formal meanings. Broadly, a well-calibrated forecaster should not label events 80% likely if only half of such events occur over time. The technical details vary, but the language teaches an important habit: confidence should match observed reliability.

126. Overconfidence is a probability-language failure | overconfidence

Overconfidence occurs when expressed certainty exceeds actual reliability or evidence. Lexically, it appears when writers upgrade possible to likely, suggests to proves, or estimate to fact. This lesson’s entire system is partly an anti-overconfidence toolkit.

127. Underconfidence can also distort communication | underconfidence

Too much caution can obscure well-established facts. If strong evidence supports a conclusion, writing “perhaps it might possibly be” weakens clarity. Calibration means neither exaggerating uncertainty nor manufacturing it. Good English is exactly as certain as the evidence permits.

128. Confidence and evidence should be linked explicitly | because / based on

“We are moderately confident because the estimate is based on three independent datasets.” “Confidence is limited because the sample is small and model assumptions are uncertain.” These sentences are stronger than naked labels such as “high confidence” because they expose the basis of the judgment.

129. Uncertainty sources should be listed, not blended | source map

A forecast may be uncertain because of measurement error, sparse data, model choice, scenario assumptions, future behaviour and external shocks. Calling the whole situation “uncertain” is sometimes enough for a short conversation. In a technical report, separate sources so readers can see which uncertainty might be reduced and which cannot.

130. Unknown unknowns is a rhetorical planning phrase, not a measurement | unknown unknowns

The phrase unknown unknowns is used in risk and planning discussions for factors not currently recognised. It can be useful rhetorically but is not itself a quantifiable uncertainty category. Do not use it as a substitute for identifying known sources of uncertainty.

131. Residual uncertainty is what remains after analysis | residual uncertainty

After measurement, modelling and sensitivity checks, some uncertainty may remain. Residual uncertainty can name that remainder. It is a useful concept because decision-making rarely waits for perfect knowledge. The question becomes whether the remaining uncertainty is acceptable for the decision at hand.

132. Decision-relevant uncertainty is the uncertainty that could change the choice | decision relevance

Not every uncertainty matters equally. If two options remain preferable under every plausible scenario, reducing one small uncertainty may not change the decision. If the decision flips when one uncertain parameter changes slightly, that uncertainty is highly decision-relevant. This language helps prioritise further research.

133. Value of information is a technical decision concept | value of information

Decision-analysis fields may quantify the value of information: how useful additional information would be for improving a decision. General learners can use the underlying question without the mathematics: “Would knowing more actually change what we do?” This prevents endless research that reduces uncertainty without changing action.

134. The uncertainty ledger | 不确定性账本

Source	Useful phrase	Can more information help?
small sample	estimate is imprecise	often
measurement	measurement uncertainty	sometimes
model choice	model uncertainty	sometimes
future pathway	scenario uncertainty	partly
natural variability	inherent/random variation	not always
missing mechanism	structural uncertainty	possibly
unrecognised factor	unknown factor	uncertain

135. Part III checkpoint: say what you do not know | 第三部分检查点

“Uncertain” is most useful when the reader can see what is uncertain: the outcome, probability estimate, measurement, model, assumption, future scenario or causal mechanism. Advanced uncertainty vocabulary moves from vague doubt to a structured statement: what is unknown, why it is unknown, how much it matters, and whether more information could reduce it.

Part IV — Turn probability into risk-aware decisions | 第四部分：把概率变成风险与决策语言

136. Probability describes chance; risk adds something at stake | 概率回答“多可能”，风险还问“损失是什么”

A 20% probability of a minor delay and a 20% probability of catastrophic failure share the same event probability but not the same practical significance. Risk language exists because decisions depend on more than likelihood. In ordinary English, risk signals the possibility of harm or loss. In specialised fields, the exact model may incorporate probability, consequence, exposure and other factors.

137. Consequence and severity are not probability words | consequence / severity

Consequence describes what happens if the event occurs. Severity grades how serious that consequence is. “The event is unlikely but severe” is completely coherent. Learners should resist collapsing the sentence into “high risk means high probability.”

138. Impact is broad consequence language | impact

Impact can describe positive or negative consequences: financial impact, operational impact, social impact. In risk contexts it often refers to harm magnitude, but some formal frameworks define the term more precisely. “High impact” does not mean “high likelihood.” Keep the axes separate.

139. Exposure describes contact with the source of harm | exposure

A person or asset may face high exposure because it frequently encounters the hazard or holds a large amount at stake. Exposure can increase risk, but it is not identical to probability. In finance, health and security, definitions differ; the general rule is to name what is exposed, to what, and under what conditions.

140. Vulnerability describes susceptibility | vulnerability

A vulnerable system is more susceptible to harm if a threat or hazardous event occurs. Vulnerability may arise from weak controls, fragile design, dependence or lack of redundancy. It does not itself tell us how often the event will occur.

141. Hazard and threat identify potential sources of harm | hazard / threat

Hazard often refers to a condition or source with potential to cause harm. Threat often describes a harmful actor, event or circumstance. Fields define these differently, so the public lesson keeps the distinction broad. The important lexical control is not to call every hazard “high risk” before considering likelihood and exposure.

142. Risk factor is associated with increased risk | risk factor

A risk factor is linked to higher risk in the relevant domain. It may or may not be causal. This phrase is common in health, finance and behavioural research. When paraphrasing, preserve the modest relationship: associated with increased risk is not automatically causes.

143. Risk indicator is evidence of risk, not necessarily a cause | risk indicator

An indicator may help identify elevated risk without being part of the causal mechanism. A warning light can indicate risk while not causing the underlying problem. This difference is useful in diagnostics and monitoring.

144. Risk driver suggests a factor pushing risk upward | risk driver

In business and project language, a risk driver is a factor contributing to risk. This can be more causal-sounding than indicator, so use evidence carefully. The phrase should identify what increases exposure, likelihood or severity rather than simply what correlates with failure.

145. Mitigation means reducing risk or consequences | mitigate risk

Mitigation does not necessarily eliminate the hazard or make the event impossible. A mitigation may reduce likelihood, reduce consequence, reduce exposure or improve recovery. “The control mitigates risk” is therefore broader than “the control prevents failure.”

146. Prevention is stronger than mitigation | prevent vs mitigate

To prevent an event means stop it from occurring. To mitigate risk means reduce it or reduce harm. If a measure only lowers probability, do not write that it “prevents” the event. This lexical difference is especially important in safety and policy writing.

147. Reduction is neutral and often safer | reduce risk

Reduce risk, lower the likelihood and decrease exposure are useful when the evidence supports a directional change but not elimination. The verb reduce is often better than dramatic words such as remove, eradicate or guarantee.

148. Control is a measure that manages risk | control measure

In risk and quality systems, a control is a measure designed to reduce or manage risk. A control can fail, degrade or have limited effectiveness. “A control exists” is not the same as “the risk is gone.”

149. Safeguard emphasises protection | safeguard

A safeguard protects people, assets or processes against harm. The word often sounds less technical than control. “Additional safeguards reduce the risk of accidental disclosure” is different from saying safeguards make disclosure impossible.

150. Residual risk remains after controls | residual risk

After mitigations are applied, some risk may remain. This is often called residual risk. The phrase is useful because it prevents a binary view where a control either “solves” the risk or does nothing. Many systems operate with reduced but non-zero risk.

151. Inherent risk is risk before controls in some frameworks | inherent risk

Many governance frameworks use inherent risk for risk before controls and residual risk after controls. Definitions vary, so learners should verify the local framework. The lexical contrast is still useful: baseline exposure versus the remaining risk after mitigation.

152. Risk tolerance is not the same as risk appetite | tolerance vs appetite

Organisations often distinguish risk appetite—the amount or type of risk they are willing to pursue or retain—from risk tolerance—the acceptable variation or boundary around objectives. Definitions vary by framework. Do not universalise one organisation’s glossary. What matters linguistically is that both describe acceptable risk, not event probability alone.

153. Risk limit is a concrete boundary | risk limit

A risk limit is usually more operational than appetite. It may specify a maximum exposure, loss, concentration or other measurable boundary. Crossing the limit can trigger action. This connects directly to Lesson No.034’s threshold vocabulary.

154. Risk threshold is the point at which action changes | risk threshold

“Escalate cases when the risk score exceeds 80.” Here 80 is a decision threshold, not necessarily a natural boundary in the world. A threshold can be policy-defined even when underlying risk changes continuously.

155. Trigger is the event that activates a response | trigger

A threshold may exist without immediate action. A trigger links the condition to a response: “Three failed checks trigger manual review.” The trigger is procedural. The underlying probability may remain unchanged.

156. Escalation is a response to risk, not risk itself | escalate

To escalate a case means move it to a higher level of attention, authority or response. Risk may trigger escalation when severity, uncertainty or exposure crosses a threshold. This is decision workflow language.

157. Contingency planning assumes uncertainty remains | contingency plan

A contingency plan prepares for an event that may occur. It does not imply the event is likely. Organisations often plan for low-probability high-impact events because the consequences justify preparation. This is a key reason probability and planning must remain separate.

158. Fallback is the alternative used after failure or blockage | fallback

A fallback is the route used when the preferred option fails or becomes unavailable. It is part of response architecture, not a probability label. “The fallback is manual review if automation fails.”

159. Backup is a redundant resource, not always a fallback plan | backup

A backup is often a secondary resource or copy kept available: backup server, backup file, backup generator. A fallback is the action route; the backup may be one of the resources used in that route. English distinguishes the object from the plan.

160. Redundancy can reduce risk without changing hazard | redundancy

Adding redundant components can reduce the likelihood that one failure stops the whole system. The hazard of component failure remains, but system-level risk can fall. This demonstrates why risk language often operates at multiple system levels.

161. Resilience concerns recovery and continued function | resilience

Resilience is the capacity to withstand disruption, recover or continue functioning. It differs from prevention. A resilient system may still experience failures but recover quickly. Risk management therefore includes both reducing probability and improving recovery.

162. Robustness concerns stability under changed conditions | robustness

A robust plan continues to perform reasonably when assumptions or inputs change. Robustness can reduce sensitivity to uncertainty. It is not the same as certainty; it means the decision or system remains acceptable across a range of plausible conditions.

163. Sensitivity asks what changes the risk estimate | sensitivity

“Risk is highly sensitive to demand assumptions.” This tells the reader that small changes in an input can materially alter the result. Sensitivity language is useful when probability estimates depend strongly on uncertain inputs.

164. Scenario analysis explores multiple plausible futures | scenario analysis

A scenario is a structured possible future, not necessarily a prediction. Scenario analysis may compare baseline, optimistic, pessimistic and stress cases without assigning exact probabilities. This is often preferable when probabilities are poorly known.

165. Stress scenario is deliberately severe | stress scenario

A stress scenario tests resilience under severe conditions. It does not say those conditions are likely. Confusing stress testing with forecasting is a common reasoning error. “We tested a 50% demand drop” is not “we predict a 50% demand drop.”

166. Worst case is not the same as most likely case | worst-case scenario

The worst case describes a severe adverse outcome within the scenario set. The most likely case ranks likelihood. They answer different questions. A low-probability worst case may still deserve planning.

167. Best case is not the same as expected case | best case

The best case is an optimistic boundary, not a probability-weighted forecast. “Best case, the project finishes in May; expected completion is July” is coherent. Do not replace best case with likely outcome.

168. Baseline scenario is a reference, not necessarily most probable | baseline

A baseline scenario provides a reference against which alternatives are compared. It may use current assumptions, central estimates or policy status quo. Depending on the framework, it is not necessarily the most likely scenario. Check definitions.

169. Central estimate is a middle judgment, not certainty | central estimate

A central estimate often represents a best or midpoint estimate within uncertainty. It should be accompanied by a range when the spread matters. “Our central estimate is 12%, with substantial uncertainty” is more informative than presenting 12% alone.

170. Expected loss combines likelihood and consequence in some analyses | expected loss

Decision and risk analysis sometimes use expected loss, combining outcome probabilities with losses under a defined model. This is technical and should not be improvised. In general English, learners can use the simpler distinction: likelihood tells us how often; consequence tells us how bad.

171. Expected value is technical, not “what we expect emotionally” | expected value

In probability and statistics, expected value has a mathematical definition. It is not necessarily the most likely outcome or the value someone literally expects to observe in one trial. Technical learners must follow the formal definition; general learners should recognise the phrase as specialised.

172. Decision threshold converts uncertainty into action | decision threshold

Decision-makers often act before certainty. They choose a threshold: when estimated risk exceeds a certain level, intervene; below it, monitor. The threshold can reflect costs, values, safety margins and resource constraints. It is a policy rule built on uncertainty, not proof that one side of the threshold is “safe” in an absolute sense.

173. Precaution means acting despite uncertainty | precaution

A precautionary action can be justified when evidence is incomplete but potential harm is serious. Precaution therefore does not mean the bad outcome is likely. It means uncertainty plus consequences warrant protective action.

174. Conservative assumption deliberately errs on the safer side | conservative assumption

In planning and safety, a conservative assumption may intentionally choose a cautious value to avoid underestimating risk. It is not necessarily the most probable estimate. Make this explicit so readers do not mistake prudence for prediction.

175. Safety margin creates distance from an uncertain boundary | safety margin

A safety margin provides extra room before a critical threshold. It can compensate for uncertainty in measurement, load, behaviour or model assumptions. “The design includes a 20% safety margin” does not mean failure probability is 20%.

176. Tolerable risk is a decision category | tolerable / acceptable risk

Some frameworks distinguish acceptable from tolerable risk. Meanings vary. Learners should verify the local standard rather than assuming one universal hierarchy. In general prose, both describe risk judged manageable enough under stated conditions.

177. Unacceptable risk triggers change | unacceptable risk

Calling a risk unacceptable is a normative decision, not merely a probability description. It implies current likelihood/consequence conditions exceed the organisation’s allowed boundary and action is required.

178. Trade-off means improving one objective may worsen another | trade-off

Risk decisions often involve trade-offs: greater safety may cost more; faster delivery may reduce testing time; lower probability of failure may require additional complexity. A trade-off is not itself uncertainty. It describes competing objectives under constraints.

179. Risk-benefit language should keep both sides explicit | risk-benefit balance

“Benefits probably outweigh risks” is a compound claim involving probability, value and consequence. Break it apart when precision matters: What benefit? How likely? What risk? How severe? For whom? Under what conditions? Advanced vocabulary makes the hidden dimensions visible.

180. Part IV checkpoint: decisions do not wait for certainty | 第四部分检查点

Risk-aware English links uncertain evidence to action without pretending uncertainty has disappeared. The core chain is: hazard/threat → exposure/vulnerability → likelihood → consequence → controls → residual risk → threshold → decision. Not every domain uses exactly this model, but the vocabulary gives learners a disciplined way to ask which relation is being expressed.

Part V — Mandarin-to-English uncertainty control | 第五部分：中文母语学习者的概率与不确定性转换

Mandarin has rich ways to express possibility, expectation, guesswork, confidence and risk, but the boundaries do not line up one-to-one with English. A learner who translates only the Chinese surface form may produce English that is grammatically correct yet too strong, too weak or conceptually wrong. The repair is the same principle used throughout this series: translate the relationship first, then choose the English word.

181. 可能 can mean possible, may, might, likely—or something else | 可能不是固定等于 possible

Chinese 可能 can express bare possibility, a probability judgment or a tentative forecast. “这可能发生” may be This could happen or This is possible. “他可能已经走了” may be He may/might have left. If the context strongly expects the outcome, He has probably left may be closer. The English choice depends on the degree of commitment, not the Chinese word alone.

182. 很可能 is usually likely/probably, not “very possible” | 很可能 ≠ very possible

“很可能下雨” is naturally It will probably rain or Rain is likely, not normally “It is very possible to rain.” English generally grades probability with likely, probably, highly probable rather than simply intensifying possible. This is a classic example of why translation by adjective stacking fails.

183. 不太可能 maps to unlikely / not very likely | 不太可能不是 impossible

“他不太可能来” → He is unlikely to come / He probably won’t come. The outcome remains possible. Do not translate this as He cannot come, which changes low expectation into impossibility or inability.

184. 几乎不可能 can be almost impossible or extremely unlikely | strength choice

Almost impossible is rhetorically strong and often emphasises difficulty. Extremely/highly unlikely is better when the point is event probability. “在现有条件下几乎不可能按时完成” may be It is almost impossible to finish on time under the current constraints, while “这种故障几乎不可能发生” may call for extremely unlikely if probability is the focus.

185. 一定 can be certainly, definitely, must or guaranteed—but not automatically | 一定的强度要验证

Chinese 一定 is frequently used conversationally for strong confidence. English certainly/definitely can match this, but guaranteed is much stronger and may imply an assurance or formal promise. Epistemic must can express inference: “他一定已经回家了” → He must have gone home. Translate the reasoning source—confidence, inference or guarantee—not just intensity.

186. 肯定 can be certain, definitely, affirmative or confirm | 肯定有多个词性与功能

“我肯定他会来” → I’m sure/certain he’ll come. “给出肯定答复” → give an affirmative answer. “确认结果” may be confirm the result, not “make it certain”. The Chinese family combines certainty, positivity and confirmation; English separates them.

187. 大概 may mean probably or approximately | 大概先问：事件还是数量？

“他大概会来” → He’ll probably come. “大概有三十人” → There are about/approximately thirty people. One Chinese expression covers event probability and numerical approximation. English normally uses different vocabulary. This distinction prevents awkward sentences such as “probably thirty people” when approximate quantity is intended.

188. 大约 is usually approximation, not event probability | about / approximately

“大约 20%” → about/approximately 20%. “大约下午三点” → around three o’clock. These words communicate imprecision in a quantity or time. They do not mean the event itself is uncertain in the probability sense. Approximation and probability can coexist but should not be conflated.

189. 也许 / 或许 map to maybe, perhaps, may or might | tentative possibility

These Chinese markers often express tentative possibility. Maybe is common in speech; perhaps can sound slightly more formal; may/might integrate uncertainty into the clause. None has a universal fixed probability. Choose by grammar and register.

190. 应该 can express duty or expectation | 应该 = should, but which should?

“你应该休息” → You should rest (advice). “火车应该六点到” → The train should arrive at six (expectation). “他现在应该到了” → He should have arrived by now (probabilistic expectation). The English word may be the same, but the reasoning function differs. Learners should hear whether should is normative or epistemic.

191. 估计 can be estimate, expect, probably or guess | 估计不是 one word

“估计损失” → estimate the loss. “我估计他不会来” → I don’t think he’ll come / He probably won’t come / I expect he won’t come, depending register. “只是估计” → only an estimate. Separate numerical estimation from informal prediction.

192. 猜 can be guess, speculate or infer depending evidence | 猜测强度

A guess may have little evidence. Speculate often means propose possibilities without firm evidence. Infer means draw a conclusion from evidence. Chinese 猜/推测 can cover several of these. If evidence exists, infer may be more accurate than guess; if the claim is exploratory, speculate may fit.

193. 推测 can be infer, conjecture, speculate or presume | 推测先问证据基础

“根据痕迹推测” may be infer from the evidence. “没有足够证据，只能推测” may be speculate. Conjecture is more formal and often theoretical. Presume can mean accept as likely based on reasonable grounds. The English choice tells the reader how much evidence exists.

194. 有可能 should not automatically become likely | 有可能 = possibility

“有可能延期” → There is a possibility of delay / The project may be delayed. Unless context indicates high probability, do not strengthen it to The project is likely to be delayed. This is one of the most common claim-inflation errors in bilingual writing.

195. 有机会 can mean opportunity or probability | 有机会的两条路线

“有机会参加” → have a chance/opportunity to participate. “有机会赢” can mean have a chance of winning, which introduces probability. Context decides whether chance is opportunity, probability or both.

196. 可能性 may be possibility or likelihood | 可能性先问是否在分级

“存在这种可能性” → This possibility exists / This cannot be ruled out. “成功的可能性很高” → The likelihood/probability of success is high. If the sentence grades the degree, likelihood/probability may be more natural; if it merely opens an outcome, possibility often fits.

197. 概率 is probability, but everyday English may prefer chance | register matters

“成功概率为 60%” → The probability of success is 60%. In ordinary conversation, “There’s about a 60% chance of success” may sound more natural. Advanced control includes moving between formal and accessible registers without changing the number.

198. 几率 can be chance, probability or odds | 几率不是 always odds

“成功几率” → chance/probability of success. Odds has a particular mathematical and betting history and is not simply a sophisticated replacement for probability. Use odds where the phrase is conventional: the odds of winning, the odds are against us.

199. 风险 normally carries negative stakes | 风险不是一般 uncertainty

“存在风险” → There is a risk when a bad outcome or loss is possible. If the future is simply unknown with both positive and negative outcomes, uncertainty may be more accurate. Do not label every unknown as a risk.

200. 危险 is danger/hazard, not automatically risk | 危险 vs 风险

A dangerous condition can be a hazard or source of danger. Risk asks how the hazard interacts with exposure, probability and consequence in the relevant framework. “This chemical is hazardous” and “The risk is low under controlled use” can both be true.

201. 威胁 maps to threat | threat ≠ probability

“安全威胁” → security threat. A threat can be serious even when its probability is not yet known. “The threat is credible” means it merits belief/attention, not necessarily that the event is highly probable.

202. 隐患 may be latent hazard, vulnerability or risk | 隐患先找机制

Chinese 隐患 can describe a hidden condition that may later cause harm. In English, the best translation might be latent hazard, safety concern, vulnerability, hidden risk depending on the mechanism. Avoid defaulting to “hidden danger” in professional prose when a more precise systems term is available.

203. 不确定 can mean uncertain, unknown or indeterminate | knowledge-state distinction

“结果不确定” → The outcome is uncertain. “原因不确定” may be The cause is unknown/uncertain. “检测结果不确定” in a technical setting may be indeterminate if that is the formal category. English often distinguishes a broad uncertain state from a formally unresolved classification.

204. 不清楚 usually means unclear / unknown, not unlikely | 不清楚 ≠ 不可能

If you do not know whether an event is common, say “The likelihood is unclear/unknown,” not “The event is unlikely.” Lack of knowledge should not become low probability through translation.

205. 没把握 often describes confidence, not event probability | confidence state

“我没把握” → I’m not confident / I’m not sure. This describes the speaker’s epistemic state. It does not necessarily mean the event probability is low. You can be unsure about an event that is objectively very likely because you lack information.

206. 有把握 can be confident / reasonably sure | confidence vs guarantee

“我有把握完成” → I’m confident I can finish it. Do not automatically write “I guarantee I will finish,” which turns personal confidence into a promise or assurance. The English verb changes social and legal force.

207. 信心 maps to confidence but needs an object | confidence in / about

“对模型有信心” → have confidence in the model. “有信心完成任务” → be confident about completing the task / confident that we can complete it. Statistical confidence is a different technical system. Mark the domain if confusion is possible.

208. 可信 can be credible, reliable or trustworthy | 可信 ≠ likely

A credible explanation is believable. A reliable measurement performs consistently or dependably. A trustworthy source deserves trust. None directly means the event is probable. “The witness is credible” is not “the event is likely.”

209. 合理 can be reasonable, plausible or justified | 合理不是 probability word

“一个合理解释” may be a reasonable/plausible explanation. “一个合理决定” may be a justified/reasonable decision. The Chinese adjective can describe logic, fairness or plausibility. English probability should not be introduced unless the context actually grades likelihood.

210. 可行 is feasible / viable, not likely | 可行回答“做不做得到”

“方案可行” → The plan is feasible/viable. This evaluates practical achievability. Whether the plan is likely to be adopted is a separate question. A feasible plan can remain politically unlikely, financially unattractive or strategically undesirable.

211. 前景 often maps to prospects or outlook | future evaluation, not raw probability

“就业前景” → employment prospects. “经济前景” → economic outlook. These phrases describe expected future conditions broadly; they are not simply probability nouns. They may combine likelihood, value and trend.

212. 预期 can be expected, anticipated or projected | source of expectation matters

“预期增长” → expected growth. “预计收入” may be projected revenue when modelled. Anticipated can signal expectation or planning. Choose the word based on whether the future value comes from a forecast, plan, model or general expectation.

213. 预测 can be forecast, predict or projection | noun/verb distinctions

Forecast is common for weather, demand and economic variables. Predict is broad. Projection often shows what would happen under assumptions rather than a direct forecast. “Under the baseline assumptions, the projection reaches 120” does not necessarily mean 120 is the most likely outcome.

214. 估算 is estimate, not exact calculation | estimate vs calculate

“估算风险” → estimate risk. “精确计算” → calculate precisely. An estimate may be model-based and sophisticated; it is not “just a guess.” But calling something an estimate signals uncertainty or approximation that an exact figure can hide.

215. 不排除 maps well to cannot rule out | non-exclusion, not likelihood

“不排除人为错误” → Human error cannot be ruled out. This sentence says the explanation remains possible. It does not say human error is likely, probable or the leading explanation. The phrase is valuable because it keeps the evidence ceiling low.

216. 倾向于 can describe tendency, preference or inclination | tend to / be inclined to

“数据倾向于支持…” might be better as The data tend to support… only if a repeated pattern exists. “他倾向于选择…” → He tends to choose / is inclined to choose… This is not a direct probability statement about one future event.

217. 大概率 is colloquial Chinese, but English needs register control | high probability / likely

Colloquial “大概率会…” often maps naturally to will probably… / is likely to…. Formal with high probability belongs to more quantitative or technical contexts. Avoid literalising the Chinese phrase into technical English when the source is conversational.

218. 小概率 means low probability, not impossible | low-probability event

“小概率事件” → low-probability event / rare event, depending context. If the consequence is severe, the event may still be operationally important. Do not dismiss it simply because it is uncommon.

219. 五五开 can be fifty-fifty / an even chance only when evidence supports balance | 五五开不是“不知道”

Chinese 五五开 may be used casually for an evenly matched situation. English fifty-fifty or an even chance makes the equality explicit. If you merely lack information, say the outcome is uncertain; do not manufacture equal probabilities.

220. 风险很高 does not automatically mean “very likely” | high risk ≠ high probability

If the possible consequence is catastrophic, a low-probability event may still receive a high risk rating in a framework. Translate the risk category as risk, not probability, unless the source explicitly defines high risk only by likelihood.

221. 风险增加 can hide absolute vs relative changes | increased risk

“风险增加一倍” may mean relative risk doubled, which can sound dramatic. If the base rate rises from 1% to 2%, the absolute increase is one percentage point. When communicating risk, preserve the baseline whenever it changes interpretation.

222. 可能增加 is weaker than likely to increase | may increase vs likely to increase

“X 可能增加 Y” → X may increase Y if only possibility is supported. “X 很可能增加 Y” → X is likely to increase Y. If evidence establishes an effect, simple present may be justified: X increases Y. These are different evidence ceilings.

223. 基准 / 乐观 / 悲观情景 are scenario labels, not probability rankings | scenario labels

Baseline, optimistic and pessimistic scenarios describe structured assumptions. They need not correspond to most likely, second most likely and least likely. If probabilities are assigned, state them separately.

224. 最坏情况 is worst case, not most likely | worst case

“最坏情况下损失 20%” → In the worst case, losses reach 20%. This says nothing about how likely that outcome is. A worst-case scenario can be deliberately extreme and still useful for resilience planning.

225. Part V checkpoint: translate the uncertainty relation | 第五部分检查点

When Chinese uses 可能, 很可能, 大概, 应该, 估计, 推测, 风险, 不确定, 把握, 可信, 可行, 预期 or 最坏情况, ask four questions before choosing English: Is this about possibility, likelihood, knowledge state, or decision consequence? Then ask whether the source is conversational, academic, technical or institutional. Relation-first translation prevents the most dangerous error in this domain: turning “we cannot rule it out” into “it will probably happen.”

Part VI — Cross-domain transfer, diagnostics and mastery | 第六部分：跨领域迁移、诊断与真正掌握

The final test is transfer. A learner who can define likelihood but cannot preserve uncertainty while summarising a research result does not yet control the word. A learner who understands risk in a glossary but calls every unlikely event “low risk” has not separated likelihood from consequence. This part moves the vocabulary through real reasoning jobs, then turns the whole lesson into a reusable diagnostic and retrieval system.

226. Research case: plausible is not probable | 研究案例一

A study finds a surprising difference between two groups. One explanation is that the intervention changed behaviour; another is that the groups differed before the intervention. Both explanations may be plausible. Calling the intervention explanation “probable” requires comparative evidence. A strong sentence might be: “One plausible explanation is that the intervention changed behaviour, although baseline differences cannot be ruled out.” The sentence keeps possibility, evidence and uncertainty aligned.

227. Research case: cannot rule out is not likely | 研究案例二

A paper says “Residual confounding cannot be ruled out.” Unsafe paraphrase: “Residual confounding probably explains the finding.” The original only says the explanation remains possible. Better: “The authors note that residual confounding remains a possible explanation.” This is a direct test of whether the learner respects non-exclusion language.

228. Research case: no evidence is not evidence of no effect | 研究案例三

A small study reports no statistically clear difference. Weak summary: “The treatment has no effect.” Stronger: “The study did not find clear evidence of an effect.” The second sentence preserves the possibility that the study lacked power or precision. If stronger evidence genuinely supports a negligible effect, the wording can become firmer. The evidence ceiling should control the claim.

229. Forecast case: expected does not mean guaranteed | 预测案例

A report states “Demand is expected to rise by 8%.” A learner rewrites “Demand will rise by 8%.” The forecast has become a fact. Better: “Demand is forecast to rise by about 8% under the baseline assumptions.” The revised sentence preserves both expectation and conditionality.

230. Project case: low probability, high impact | 项目案例

A data-centre outage is estimated to be uncommon, but if it occurs the project could stop for days. The team therefore treats it as a serious risk and maintains a backup system. The correct explanation is not “an outage is very likely.” It is: “The outage is unlikely, but its potential impact is severe enough to justify contingency planning.” This sentence separates likelihood, consequence and decision.

231. Cybersecurity case: threat, vulnerability and risk | 技术案例

A phishing campaign is a threat. Weak authentication is a vulnerability. Employees receiving many suspicious messages increases exposure. The probability of compromise depends on controls and behaviour. The business risk depends on the likelihood and consequences of compromise. These terms should not be collapsed into “there is a cyber risk.” A detailed risk statement reveals where intervention is possible.

232. Engineering case: hazard is not risk | 工程案例

A high-voltage component is hazardous because it can cause harm. Insulation, access controls and shutdown systems may reduce exposure and probability. The hazard remains while operational risk falls. This distinction explains why “remove the risk” can be misleading when the source of harm still exists.

233. Weather case: 70% probability does not mean 70% of the day | 天气概率案例

Probability statements require the source’s definition. A 70% chance of rain does not automatically mean rain for 70% of the day, 70% of the city or 70% intensity. When communicating weather probabilities, preserve the issuing service’s stated meaning rather than inventing an intuitive interpretation.

234. Examination case: possible explanation vs likely explanation | 考试案例

If a passage gives one clue that a character may be anxious, an answer can say “This suggests that she may be anxious.” If several strong clues make anxiety the leading interpretation, “She is likely anxious” may become defensible. The answer should scale probability language to textual evidence rather than using “definitely” for every inference.

235. Reading comprehension: small modal words change the proposition | 阅读理解案例

“The policy may reduce costs” is not equivalent to “The policy reduces costs.” “The policy is likely to reduce costs” is stronger than “may reduce.” “The policy will reduce costs” is stronger again unless will is part of a conditional or procedural description. Good comprehension includes the modal because the modal is part of the meaning.

236. Summary writing: preserve probability while compressing | 摘要案例

Original: “The authors suggest that the intervention may improve short-term retention, although long-term effects remain uncertain.” Unsafe summary: “The intervention improves retention.” Better: “The intervention may improve short-term retention, but long-term effects are uncertain.” The shorter version keeps claim strength and time horizon.

237. Paraphrase: suggests cannot become demonstrates | 改述案例

Original: “The pattern suggests a possible threshold effect.” Unsafe paraphrase: “The data demonstrate a threshold effect.” Two upgrades have occurred: suggests → demonstrates and possible → established. A safe paraphrase might be “The pattern is consistent with a possible threshold effect.” Meaning-preserving paraphrase protects uncertainty twice: evidential verb and probability marker.

238. Oral discussion: repair overstatement in real time | 口语实时修正

A learner says, “This will definitely fail—sorry, I mean it is likely to fail if the load stays above 90%.” That self-repair is sophisticated. Advanced speaking is not zero error; it is the ability to recalibrate quickly when the first wording exceeds the evidence.

239. Parent communication: simplify without deleting uncertainty | 家长沟通案例

Technical: “The probability of improvement is uncertain because baseline data are sparse.” Parent-friendly: “We do not yet have enough information to say how likely improvement is.” The second sentence is simpler but preserves the knowledge state. Plain English should remove jargon, not uncertainty itself.

240. Data storytelling: relative change needs baseline | 数据叙事案例

“Risk doubled” sounds large. If the probability moved from 0.5% to 1%, the absolute increase is 0.5 percentage points. A fair explanation reports both when the baseline changes interpretation. Advanced vocabulary should resist sensational framing even when the mathematics is technically correct.

241. Decision case: unknown is not fifty-fifty | 决策案例一

Two suppliers are under consideration. There is almost no reliability data for Supplier B. It is wrong to say “B has a 50% chance of being reliable” merely because there are two possible labels: reliable/unreliable. The correct statement is “B’s reliability is uncertain because evidence is insufficient.” Ignorance is a knowledge gap, not a probability distribution.

242. Decision case: most likely can still be below 50% | 决策案例二

Three delivery dates have estimated probabilities: June 40%, July 35%, August 25%. June is the most likely date, but a June delivery is still less likely than “not June” collectively. This case is useful because it breaks the intuitive but false equation most likely = more likely than not.

243. Decision case: high risk can come from severe consequence | 决策案例三

A failure has only a 1% annual probability but could cause extremely large losses. The organisation may classify the risk as high. A second event has an 80% chance of causing a five-minute delay and may be operationally minor. Probability alone does not determine practical risk.

244. Decision case: potential does not mean probable | 决策案例四

“This change has the potential to reduce costs by 20%” means the saving is possible under appropriate conditions. It does not say a 20% saving is expected. Before converting potential into forecast, ask for the mechanism, assumptions and evidence.

245. Decision case: scenario is not forecast | 决策案例五

A team tests a scenario in which demand falls 40%. That figure may be deliberately severe rather than probable. The correct report is “We tested resilience under a 40% demand-drop scenario,” not “We expect demand to fall 40%.” Scenario design and forecasting are separate jobs.

246. Evidence update case: new information should change confidence | 更新案例

Initial estimate: “Delay is possible but not expected.” New evidence: a supplier reports a major production problem. Updated estimate: “Delay is now likely.” The vocabulary should move when evidence moves. Refusing to update is as inaccurate as changing confidence without evidence.

247. Calibration case: confidence needs a track record | 校准案例

If a forecaster repeatedly calls events “almost certain” but they occur only half the time, the language is poorly calibrated. A learner can practise calibration without sophisticated statistics: record predictions, confidence labels and outcomes, then compare whether “likely” events truly occur more often than “possible” events.

248. Build the uncertainty FENCE | 概率与不确定性 FENCE

Fence	Question	Language job
F0 Event	What exact outcome are we discussing?	define event
F1 Possible	Can it happen?	possible / cannot rule out
F2 Likelihood	How likely is it?	probability / likely / unlikely
F3 Evidence	What supports the estimate?	data / source / model
F4 Uncertainty	What remains unknown?	estimate / model / scenario uncertainty
F5 Risk	What bad outcome matters?	risk / exposure / vulnerability
F6 Consequence	How serious would it be?	impact / severity / loss
F7 Threshold	When does action change?	trigger / limit / precaution
F8 Transfer	Can I preserve all this in a new context?	paraphrase / speaking / decision

249. Build an uncertainty-control card | 不确定性控制卡

Field	Example
Event	supplier misses deadline
Possible?	yes
Likelihood	currently moderate / uncertain
Evidence	two late milestones
Unknown	supplier recovery capacity
Consequence	two-week launch delay
Mitigation	secondary supplier prepared
Residual risk	some delay remains possible
Trigger	missed third milestone
Action	activate fallback supplier

250. Practice A — possibility or likelihood? | 练习 A

1. The event cannot be excluded, but no evidence suggests it is common.
2. Past data show the outcome occurs in roughly three quarters of comparable cases.
3. A scenario is logically possible but requires several unusual conditions.
4. Among three outcomes, A has the highest estimated probability at 40%.
5. The probability cannot yet be estimated because data are sparse.

For each item, choose language such as possible, likely, most likely, uncertain, cannot be ruled out without adding stronger commitment than the evidence permits.

251. Practice B — risk or uncertainty? | 练习 B

6. We do not know whether next month’s demand will rise or fall.
7. There is a small chance of a fire that could destroy the warehouse.
8. The model’s estimate varies widely across assumptions.
9. The system is vulnerable because it has no backup power.
10. The exact probability of failure is unknown.

252. Practice C — choose the probability marker | 练习 C

11. The data only keep X open as one explanation.
12. Repeated evidence makes X the leading explanation.
13. X ranks first among four explanations but has an estimated probability of 35%.
14. X has an estimated probability close to 95% under the model.
15. No credible pathway exists under the stated rules.

253. Practice D — preserve the evidence ceiling | 练习 D

Rewrite each unsafe sentence:

16. “The study proves the cause.” Original source: “The findings suggest a possible causal pathway.”
17. “The project will be delayed.” Original source: “Delay cannot be ruled out.”
18. “The system is safe.” Original source: “Residual risk is low under current operating conditions.”
19. “Failure is impossible.” Original source: “Failure is highly unlikely.”
20. “The forecast is accurate.” Original source: “The model is well calibrated in historical validation.”

254. Practice E — high probability or high risk? | 练习 E

21. 90% chance of a five-minute delay.
22. 1% chance of catastrophic data loss.
23. 40% chance of a moderate cost overrun.
24. Unknown probability of a severe external event.
25. 70% chance of a harmless warning message.

Do not rank the cases from probability alone. Explain what additional consequence, exposure and control information is needed before assigning a risk level.

255. Practice F — Mandarin translation repair | 练习 F

26. 这个方案很可能成功。
27. 这个方案有可能成功。
28. 我没把握它会成功。
29. 这个方案可行，但不一定会获批。
30. 最坏情况下，成本会上升 30%。
31. 不排除供应链问题。
32. 这个风险很高，但发生概率很低。

256. Practice G — relative and absolute risk language | 练习 G

A probability increases from 2% to 3%. Write four correct descriptions: the new probability; the absolute increase in percentage points; the relative increase; and a plain-English version that includes the baseline. Then explain why “risk rises by 50%” without the baseline can be misleading.

257. Reference answers — selected items | 参考答案

• Practice A1: The event is possible / cannot be ruled out.
• Practice A2: The outcome is likely under comparable conditions.
• Practice A4: A is the most likely single outcome, although its probability is below 50%.
• Practice A5: The likelihood is currently uncertain / cannot yet be estimated reliably.
• Practice D2: The project may be delayed; delay cannot be ruled out.
• Practice D3: Residual risk is low under current operating conditions.
• Practice D4: Failure is highly unlikely, but not impossible.
• Practice G: 3% probability; +1 percentage point; +50% relative to 2%; “The estimated probability rose from 2% to 3%.”

258. A 15-minute uncertainty session | 15 分钟训练

Time	Task
0–3 min	Choose one uncertain event.
3–6 min	Write possible / likely / unlikely versions.
6–9 min	Name the evidence and unknowns.
9–12 min	Add consequence and risk language.
12–15 min	Explain the decision threshold aloud.

259. A 30-minute calibration workshop | 30 分钟校准训练

Time	Task
0–5 min	Collect ten uncertainty phrases from authentic text.
5–10 min	Classify possibility / likelihood / evidence / risk.
10–15 min	Rank commitment without inventing percentages.
15–20 min	Paraphrase while preserving strength.
20–25 min	Convert technical phrasing to plain English.
25–30 min	Retrieve the distinctions without notes.

260. A seven-day uncertainty challenge | 七天训练

Day	Focus
1	possible / likely / probable / unlikely
2	may / might / could / must / should
3	uncertainty / confidence / estimate / precision
4	risk / hazard / threat / vulnerability / exposure
5	mitigation / residual risk / threshold / contingency
6	Mandarin false-equivalence repair
7	full FENCE transfer case

261. A 30-day probability-language challenge | 30 天系统升级

• Collect 50 authentic probability/uncertainty sentences.
• Repair 20 possible-versus-likely errors.
• Repair 20 unknown-versus-unlikely errors.
• Build 20 risk statements separating likelihood and consequence.
• Rewrite 15 forecasts with assumptions and ranges.
• Complete 15 “cannot rule out” paraphrase drills.
• Write 10 relative-versus-absolute probability explanations.
• Maintain a forecast journal and compare confidence with outcomes.
• Explain 10 cases orally without dropping uncertainty markers.

262. A 12-week progression | 12 周路线

Weeks	Focus	Mastery evidence
1–2	possibility vs likelihood	no “possible = likely” inflation
3–4	modals and verbal probability	controlled commitment
5–6	uncertainty sources and confidence	can name what is unknown
7–8	risk architecture	separates likelihood/consequence
9–10	Mandarin transfer and quantitative framing	fewer false equivalents
11–12	cross-domain independent control	preserves uncertainty in new tasks

263. The first weak-link diagnostic | 第一个弱点诊断

Symptom	Likely weakness	Repair
I use possible and likely interchangeably.	commitment scale	possible vs expected contrast
I say 50-50 whenever I do not know.	ignorance/probability confusion	unknown vs even chance
I call low-probability events low risk.	likelihood/consequence confusion	risk two-axis cases
I treat confidence as probability.	judge/event confusion	confidence vs event likelihood
I turn cannot rule out into probably.	evidence ceiling	non-exclusion drills
I use worst case as forecast.	scenario/forecast confusion	scenario labels
I quote relative risk without baseline.	quantitative framing	absolute + relative pair
I drop modals when summarising.	uncertainty cohesion	boundary-preserving summary

264. How a strong tutor teaches probability vocabulary | 高水平导师怎样教？

A weak lesson gives a ladder: maybe → probably → definitely. A stronger lesson presents evidence and asks the learner to choose the weakest expression that remains accurate. Then it changes the evidence and asks the learner to update. Next, it adds consequences and asks whether risk changes even if probability does not. Finally, it removes data and asks the learner to say “unknown” rather than invent 50-50. The tutor teaches calibration, not vocabulary decoration.

265. The learner should become their own uncertainty editor | 自我编辑

Before finalising an uncertain claim, ask: Have I confused possible with likely? Have I turned missing information into low probability? Did I remove a modal during paraphrase? Does my confidence word describe the evidence or only my feeling? If I call something high risk, have I separated likelihood from consequence? If I give a percentage, where did it come from? These questions catch many advanced errors before publication.

266. Canonical ownership and collision boundary | 本课所有权边界

This lesson owns the Mandarin-supported C1–C2 lexical architecture of possibility, probability, likelihood, chance, odds, uncertainty, confidence, risk and decision language under incomplete knowledge. It coordinates but does not replace:

• Lesson No.020 — broad stance, hedging and evaluation strength.
• Lesson No.029 — degree, intensity and scalar vocabulary.
• Lesson No.032 — causation, contribution and association.
• Lesson No.033 — evidence, findings, claims and conclusions.
• Lesson No.034 — conditions, constraints, caveats and thresholds.

267. Recommended reference floor | 推荐参考资源

• Cambridge Dictionary — probability — degree/level of possibility and common patterns.
• Cambridge Dictionary — likelihood — chance that something will happen.
• Cambridge Dictionary — possibility — event possibility and option sense.
• Cambridge Dictionary — risk — possibility of something bad happening.
• Cambridge Dictionary — uncertainty — situation in which something is not known or certain.
• Cambridge Dictionary — likely — expected/probably going to happen; grammar patterns.
• Oxford Advanced Learner’s Dictionary — likelihood — likelihood phrases and examples.
• Oxford Advanced Learner’s Dictionary — odds — probability and idiomatic patterns.
• Oxford Advanced Learner’s Dictionary — certainty — certainty, degrees and near-certainty expressions.
• University of Manchester Academic Phrasebank — Being cautious — cautious probability, modal and claim language.
• University of Manchester Academic Phrasebank — Discussing Findings — explanation, interpretation and uncertainty.

268. SEO language map | 本课关键词范围

This lesson naturally serves probability vocabulary English, likelihood vs possibility, possible vs likely, probability vs uncertainty, risk vs probability, chance vs odds, likely vs probable, may might could probability, uncertainty academic English, confidence vs certainty, high risk vs high probability, relative risk vs absolute risk, verbal probability English, C1 C2 probability vocabulary, advanced English for Chinese speakers, 英语概率词汇, possible likely 区别, probability likelihood possibility 区别, risk uncertainty 区别, 可能性英语, 风险英语, 不确定性英语, 中文母语高级英语, C1 英语 and C2 英语.

269. Your assignment | 本课作业

Choose one genuinely uncertain real-world decision that you understand well—a project deadline, exam preparation plan, business forecast, technical reliability question or another non-sensitive case. Build a complete uncertainty map.

1. Define the exact event.
2. State whether it is possible.
3. Estimate likelihood only if evidence supports doing so.
4. Name the evidence source.
5. List what remains unknown.
6. Separate outcome uncertainty from estimate uncertainty.
7. Identify any relevant base rate.
8. Describe the consequence if the adverse event occurs.
9. Separate likelihood from severity.
10. Identify exposure and vulnerability where relevant.
11. List mitigations and controls.
12. Describe residual risk.
13. State the decision threshold or trigger.
14. Write one technical version.
15. Write one plain-English version.
16. Explain it aloud in 90 seconds without losing probability markers.
17. Two days later, reconstruct the FENCE from memory.

270. The longform return | 为什么这篇需要长？

The reader job is not “learn ten synonyms for maybe.” It is to build a system that can survive reading, writing, quantitative claims, translation, research, project planning and decision-making. A short list cannot teach why an unknown probability is not 50-50, why a most-likely outcome can be below 50%, why high risk can coexist with low probability, why cannot rule out is weaker than likely, or why a worst-case scenario is not a forecast. Depth earns its place when it prevents those reasoning failures and gives the learner a reusable repair process.

271. Final rule | 最后一条规则

Say “possible” when the door is open. Say “likely” when the outcome is expected. Say “uncertain” when knowledge is incomplete. Say “risk” when something valuable may be lost.

结果只是“可能发生”时，就说 possible；证据让它成为预期结果时，才说 likely；知识不完整时，说 uncertain；当坏结果可能带来损失时，才进入 risk。

Probability tells you how likely. Uncertainty tells you how well you know. Risk tells you why the outcome matters.

probability 告诉你有多可能；uncertainty 告诉你知道得有多清楚；risk 告诉你为什么这个结果值得在意。

Do not turn possibility into prediction. Do not turn ignorance into fifty-fifty. Do not turn a low-probability catastrophe into “low risk” without examining consequence. Do not turn a confident voice into strong evidence. And do not add a precise percentage merely because a precise number looks more intelligent.

The most advanced uncertainty language is not the language that sounds least certain. It is the language whose degree of certainty matches what the evidence actually permits.

Series: EDKS-ADV-VOC-ZH · Lesson 035.