Logical Reasoning Inference & Resolution: Proving What Follows and Fixing What Conflicts

Must Be True

What it is

A Must Be True (MBT) question asks you to identify a statement that is logically forced by the stimulus. If the stimulus is true, the correct answer cannot be false—it must hold in every possible world consistent with what you were told.

Think of MBT as reading a set of rules or facts and then asking, “What has to follow from this, no matter what else is going on?” You are not being asked what is likely, sensible, or typical. You are being asked what is deductively entailed.

Why it matters

MBT questions train the core Logical Reasoning skill: drawing valid inferences while resisting tempting assumptions. On the LSAT, many wrong answers sound reasonable because they match real-world expectations, but MBT rewards only what is proven by the text.

MBT is also the “anchor” inference type—once you get comfortable with what must follow, it becomes easier to understand neighboring types like Most Strongly Supported (weaker than “must”) and Cannot Be True (the flip side of “must”).

How it works (a reliable process)

1. Treat the stimulus as a closed universe. Your job is not to improve the argument or bring in outside knowledge. Only use what’s stated and what logically follows.
2. Separate facts from conclusions. Many MBT stimuli are not “arguments” at all—just a set of statements. Even if there is a conclusion, you still can only infer what’s guaranteed.
3. Look for “linking” opportunities. The most common way to get a must-inference is to combine two statements:
   • A general rule + a specific case
   • Two conditional statements that chain
   • A universal claim + an exception statement
   • A comparison that forces an ordering
4. Be strict with quantifiers and wording. Words like “all,” “some,” “most,” “many,” “only,” and “unless” matter. A classic MBT trap is an answer that strengthens “some” into “most” or “all.”
5. Use the “denial test.” For a candidate answer, ask: Could the stimulus still be true if this answer were false? If yes, it’s not must-be-true.

Foundational inference moves you’ll use constantly

Conditional reasoning (if–then)

• If you have: If A, then B
  • You may infer: If not B, then not A (the contrapositive).
  • You may not infer: If B, then A (affirming the consequent).
  • You may not infer: If not A, then not B (denying the antecedent).

MBT answers often amount to a contrapositive or a chained conditional.

“Only if” vs “if”

• “A only if B” means: If A, then B.
• “A if B” means: If B, then A.

Quantifiers

• “Some” means at least one.
• “Most” means more than half.
• “All” means 100%.

Valid inference examples:

• From “All cats are mammals,” you can infer “No cats are non-mammals.”
• From “Some cats are black,” you can infer “At least one cat is black.” (Nothing stronger.)

Must Be True in action (worked examples)

Example 1: Chaining conditionals

Stimulus:

Any employee who handles cash must complete the security training. Rosa handles cash. No one who has not completed the security training may work the closing shift.

Reasoning:

• “Handles cash \u2192 completed training.”
• Rosa handles cash \u2192 Rosa completed training.
• “Not completed training \u2192 may not work closing shift.”
• That second rule doesn’t directly tell you Rosa works closing, but it does let you infer: if someone works closing, they completed training (contrapositive).

A statement that must be true:

Rosa has completed the security training.

Why it’s must: if Rosa hadn’t completed training, the first rule would be violated.

Trap to notice: An answer like “Rosa may work the closing shift” is possible but not guaranteed.

Example 2: Quantifiers and overreach

Stimulus:

Some of the committee members are engineers. All engineers on the committee have read the proposal.

A statement that must be true:

Some of the committee members have read the proposal.

Why: at least one committee member is an engineer, and every engineer on the committee read it—so at least one committee member read it.

Common wrong answers here:

• “All committee members have read the proposal” (too strong)
• “Most committee members are engineers” (adds quantity)

Exam Focus

Typical question patterns

• “Which of the following can be properly inferred from the statements above?”
• “Which of the following is most strongly supported by the information above?” (Sometimes this wording is used even when the logic is essentially MBT—your job is still to pick what’s best supported.)
• Stimuli that are fact sets: short rules, definitions, or policy statements with one concrete case.

Common mistakes

• Treating reasonable assumptions as if they are proven (real-world filling-in).
• Confusing converse/inverse with the contrapositive in conditional logic.
• Picking an answer that is consistent with the stimulus rather than forced by it.

Most Strongly Supported

What it is

A Most Strongly Supported (MSS) question asks for the answer that is best supported by the stimulus, even if it is not proven with 100% certainty. If MBT is “must be true,” MSS is “more supported than the others.”

That does not mean MSS is about guessing or vibes. The correct answer still needs clear textual/logical backing—it’s just that the stimulus may not be tight enough to force a single deductive conclusion.

Why it matters

In real reasoning, you often draw conclusions that are well-supported but not logically guaranteed—like interpreting survey data, inferring motivations, or predicting outcomes based on patterns. The LSAT tests whether you can:

• stay grounded in evidence,
• avoid overclaiming,
• and choose the option with the strongest tie to what’s given.

MSS also helps you calibrate “strength.” Many wrong answers fail because they go one notch too strong (e.g., “all” instead of “most,” “will” instead of “likely,” “caused” instead of “associated with”).

How it works (how to choose the best-supported answer)

1. Map the support relationship. Ask: “What does the stimulus make likely?” and “What would be a safe takeaway?”
2. Prefer answers that paraphrase or lightly generalize the stimulus. The best MSS answers often look “boring”—they restate what you already basically know, sometimes with a modest inference.
3. Beware of causal leaps. If the stimulus only shows correlation or sequence, an answer that claims causation is usually too strong.
4. Use comparative elimination. Because MSS is “best of the five,” you often win by eliminating answers that:
   • introduce new actors or new time periods,
   • require outside assumptions,
   • use overly strong language.
5. Check for scope and degree. The right answer matches the stimulus’s scope (who/what it’s about) and degree (how strong the claim is).

A helpful way to distinguish MBT vs MSS

Most Strongly Supported in action (worked examples)

Example 1: Survey evidence (avoid overclaiming)

Stimulus:

In a city survey, residents who live within two blocks of a park reported exercising more frequently than residents who live farther away.

What you can safely take away:

• The survey shows an association between proximity to parks and self-reported exercise frequency.
• It does not prove the park caused the exercise (maybe active people choose to live near parks).

An MSS answer might be:

Residents living near parks tend to report exercising more frequently than residents living farther away.

A classic wrong answer:

Living near a park causes residents to exercise more.

That causal wording is stronger than the evidence.

Example 2: Small inferential step from facts

Stimulus:

The museum’s attendance increased after it extended weekend hours. During the same period, the museum also launched a major advertising campaign.

An MSS answer could be:

The increase in attendance cannot be attributed solely to the extended weekend hours.

Why this is strongly supported:

• Since another major change (advertising) happened at the same time, the stimulus supports the idea that extended hours alone don’t fully explain the rise.

Notice: This answer doesn’t claim advertising caused the increase—it just blocks an overly simple explanation.

Exam Focus

Typical question patterns

• “Which of the following is most strongly supported by the information above?”
• “The statements above, if true, most strongly support which of the following?”
• Stimuli with data, surveys, studies, trends, or multiple possible explanations.

Common mistakes

• Treating MSS like MBT and rejecting a correct answer because it isn’t perfectly proven.
• Picking an answer that is true in real life but not supported by the stimulus.
• Missing subtle overstatements: “always,” “never,” “only,” “proves,” “causes,” “guarantees.”

Cannot Be True

What it is

A Cannot Be True (CBT) question asks you to identify the statement that is incompatible with the stimulus—something that cannot be the case if the stimulus is true.

CBT is the “negative mirror” of Must Be True:

• MBT: find what must be true.
• CBT: find what must be false.

Both rely on the same skill: understanding what the stimulus commits you to.

Why it matters

CBT questions test whether you can enforce logical constraints. This is a practical skill: in planning, law, and policy, you often need to know not just what follows, but what’s ruled out. On the LSAT, CBT also rewards disciplined thinking because tempting wrong answers often seem “unlikely” or “odd,” but your job is strictly: Does the stimulus forbid it?

How it works (two main methods)

Method 1: Direct contradiction spotting

Sometimes an answer choice directly conflicts with a stated fact.

• Stimulus: “No bicycles are allowed in the park.”
• CBT answer: “At least one bicycle is allowed in the park.”

Method 2: Derive a necessary rule, then test answers

Often you must infer a constraint (like a contrapositive or a chained condition) and then see which answer violates it.

A powerful CBT technique is the Possibility Test:

• For each answer, ask: “Can I construct a scenario where the stimulus is true and this answer is also true?”
• If you can, it’s not CBT.
• If you cannot—because it breaks a rule or forces a contradiction—it’s the correct choice.

CBT and conditional logic (where many students slip)

If the stimulus contains conditionals, CBT answers frequently violate:

• the original conditional (“If A then B”) by giving A and not B, or
• the contrapositive (“If not B then not A”) by giving not B and A (same violation, different viewpoint).

Students often make the mistake of thinking “If A then B” forbids “not A.” It doesn’t. “Not A” is perfectly allowed; the rule is silent about it.

Cannot Be True in action (worked examples)

Example 1: Violate a rule

Stimulus:

All of the clinic’s nurses are certified. Some clinic employees are nurses.

We can infer:

• Some clinic employees are certified (because some are nurses, and all nurses are certified).

Which statement cannot be true?

• “None of the clinic’s employees are certified.”

That directly contradicts the inference that at least one employee is certified.

Example 2: Chaining and contradictions

Stimulus:

If the alarm is armed, the red light is on. If the red light is on, the control panel is locked.

This chains to:

• Alarm armed \u2192 red light on \u2192 control panel locked
  So:
• Alarm armed \u2192 control panel locked
  And contrapositive:
• Control panel not locked \u2192 alarm not armed

A statement that cannot be true:

The alarm is armed and the control panel is not locked.

That combination (armed + not locked) violates the chained implication.

Exam Focus

Typical question patterns

• “Which of the following cannot be true?”
• “Each of the following could be true EXCEPT…”
• Rule-heavy stimuli (policies, scheduling constraints, definitions) or conditional chains.

Common mistakes

• Eliminating an answer because it seems implausible rather than impossible.
• Forgetting that “If A then B” allows “not A” cases.
• Missing a required contrapositive and therefore failing to see the hidden contradiction.

Resolve the Paradox

What it is

A Resolve the Paradox question presents an apparent contradiction—two facts (or a fact and a trend) that seem unable to both be true. Your task is to choose an answer that shows how both can be true at the same time.

The correct answer does not have to prove which side is “right.” Instead, it supplies a missing piece that removes the conflict—often by:

• distinguishing groups,
• adding a timeline,
• introducing a third factor,
• clarifying a definition,
• or showing that a comparison is misleading.

Why it matters

Resolution questions test whether you can diagnose why something looks inconsistent. In real analysis—legal reasoning, scientific interpretation, policy evaluation—conflicts often come from hidden differences in populations, measurement methods, or baseline conditions. The LSAT rewards the habit of asking, “What would make both statements make sense?” rather than picking a side.

How it works (a step-by-step approach)

1. State the paradox clearly in your own words. Identify the two pieces that clash.
2. Identify what would have to be true to reconcile them. You are looking for a “bridge” idea.
3. Predict common resolution patterns. Most correct answers fall into a few families:

Common resolution patterns

• Different groups / selection effect: The two facts apply to different subsets.
• Different time frames: One statement is about “before,” the other about “after,” or the trend changed.
• Different measures / definitions: The metric changed (e.g., total dollars vs dollars per person).
• Hidden third variable: Something else explains both outcomes.
• Offsetting changes: One factor went up while another went down, producing a surprising net effect.

1. Check that the answer addresses both sides. A good resolution explains why fact A and fact B can both be true. Wrong answers often explain only one side.
2. Avoid answers that intensify the conflict. Some choices add another reason the situation is puzzling—those are traps.

What goes wrong (common misconceptions)

• Treating it like a weakening/strengthening question. You are not asked to attack an argument. You’re asked to make two claims compatible.
• Choosing an answer that is merely plausible. The correct choice must specifically connect to the two clashing facts.
• Missing the exact comparison. Many paradoxes depend on rates vs totals or per-unit vs overall measures.

Resolve the Paradox in action (worked examples)

Example 1: Totals vs rates

Stimulus:

This year, the city reported more bicycle accidents than last year. Yet the city also reports that bicycling has become safer.

Why it seems paradoxical:

• More accidents sounds like less safety.
• But “safer” suggests fewer accidents (or less risk).

A resolving answer:

The number of people bicycling increased substantially this year.

How it resolves:

• If many more people bike, total accidents can rise even while the accident rate per rider falls—meaning bicycling is safer on a per-person basis.

Wrong-answer patterns:

• “The city’s roads are in worse condition this year.” (That would tend to make biking less safe, worsening the paradox.)
• “Some accidents go unreported.” (Doesn’t specifically reconcile more reported accidents with greater safety unless it ties to changed reporting rates.)

Example 2: Different groups

Stimulus:

A restaurant replaced table service with counter ordering to reduce wait times. After the change, customer complaints about long waits increased.

Why it seems paradoxical:

• The policy aimed to reduce waits, but complaints increased.

A resolving answer:

After the change, the restaurant attracted many more customers during peak hours, increasing crowding near the counter.

How it resolves:

• The new system might be faster per transaction, but higher volume and bottlenecks could increase perceived waiting (or at least increase the number of people exposed to any wait).

Another plausible resolution family here would be expectation effects:

• If customers were told it would be faster, they may complain more when any wait remains. That can also reconcile “system improved” with “complaints increased.”

Exam Focus

Typical question patterns

• “Which of the following, if true, most helps to resolve the apparent discrepancy?”
• “Which of the following, if true, would best explain how both of the above statements could be true?”
• Stimuli featuring surprising results, conflicting studies, or policies that appear to backfire.

Common mistakes

• Picking an answer that explains only one fact (e.g., why accidents rose) but not why the other can still be true (why biking is safer).
• Choosing an answer that introduces a new contradiction rather than resolving the existing one.
• Missing rate-vs-total distinctions and per-capita framing—one of the most common paradox engines.