LSAT Logical Reasoning – Causation & Curious Comparisons

Curious Comparisons & the Role of Causation

  • Logical-Reasoning (LR) passages frequently present a “curious comparison / curious fact” that triggers a causal claim.
    • Readers must pause and ask “Why is that?” to anticipate arguments and answers.
    • Typical wording signals: more than, less than, tend to, higher rate, lower rate, before & after, at the same time.
  • Key skill: differentiate between merely describing a correlation and claiming a cause.

Two Broad Categories of Causal Tasks

  • (1) Author presents causal claim → we assess it
    • Question stems: Strengthen, Weaken, Flaw, Assumption, Evaluate.
    • Duties:
    • Generate alternate explanations (reverse causation, third factors, bad data, regression to mean, etc.).
    • Gauge plausibility of author’s story via covariation evidence, mechanism, or distinctiveness.
  • (2) We supply the causal explanation
    • Question stems: Resolve / Explain Paradox, Most Supported (when facts are causal), Principle Questions asking for causal chains.
    • Duties: Craft multiple plausible storylines; choose answer(s) that best resolve discrepancy.

Mini-Examples of Curious Comparisons (from official tests)

  • Small vs. Large Studies & Newspaper Coverage
    • Fact: More articles about small studies.
    • Author’s claim: Headlines are flashier → journalists prefer them.
    • Alt-explanation: \text{# of small studies} \gg \text{# of large studies}, so coverage is proportional.
  • Marked vs. Unmarked Crosswalk Injuries
    • Fact: Higher pedestrian injuries where there are stripes/lights.
    • Author’s claim: Safety measures ineffective or harmful.
    • Alt-explanation: Those were already the most dangerous crossings; stripes/lights are mitigating, not causing.
  • Label Readers vs. Non-readers & Dietary Fat %
    • Fact: Non-readers have higher fat-calorie %.
    • Multiple possible causes: health consciousness, education, income, etc.
  • Water-Heater Paradox (Jimmy)
    • Fact: Replaced old heater with “highly efficient” model, yet gas bills ↑.
    • Brainstorm four coherent storylines: uncle moved in (more people), started using a gas dryer, gas rates ↑, unusually cold weather.

Habit-Building: Always Ask

  • “Why are newspapers covering small studies?”
  • “Why more injuries at marked crosswalks?”
  • “Why is the gas bill higher with an efficient heater?”

“Explain the Paradox / Resolve” Question (Water-Heater example)

  • Correct answer (A) increased surprise → therefore wrong for Resolve-Except format (others do resolve).
  • Four resolving answers illustrate alternate stories: extra resident, new appliance, rate hike, colder weather.
  • LSAT allows common-sense connections (e.g., uncle uses shower). Avoid far-fetched links (e.g., Jimmy’s promotion).

Causal Flaw Questions

  • Core flaw: Inferring cause from correlation.
    • Pattern: evidence = correlation → conclusion = causal statement.
  • LSAT “flaw” answer phrasing template: “infers that X causes Y from evidence that X and Y are correlated.”
  • Other famous flaws (10–15): Sampling, Possible vs. Certain, Necessary vs. Sufficient, Appeal to Inappropriate Authority, etc.

Anatomy of Correlations & Their Pitfalls

  • Statistical lopsidedness
    • “Most” or “more likely” signals disproportionate representation.
  • Temporal
    • Before/After (speed limit ↑ then fatalities ↓) ⇒ correlation, not proof.
    • Simultaneous (mint bowls appear when Uber enters market).
  • When authors jump to causation, explore:
    1. Reverse Causality (Y → X).
    2. Third Factor (Z) causing X and/or Y.
    3. Bad Data / Sample / Measurement issues.

Covariation: Primary Tool to Test Plausibility

  • Strengthen: show cause & effect absent together or present together.
    • No-cause/no-effect => “When newspapers didn’t pick small studies, no extra coverage.”
    • Additional matching data points reinforce link.
    • Provide mechanism (“addressing rural distress increases turnout”).
  • Weaken: demonstrate mismatch (cause without effect or vice-versa) or competing causal story.
  • Evaluate: ask for missing piece that would most affect plausibility (often tests covariation directly).

Strengthen-Except Example (1935 Land Party)

  • Curious comparison: only national victory occurred in 1935.
  • Author’s dual hypothesis: (1) spoke to rural/semi-rural distress; (2) that bloc was especially hard-hit.
  • Answer analysis:
    • (A) Irrelevant (urban focus) → the one that fails to strengthen.
    • (B) & (E) supply mechanism or critical voter importance.
    • (C) Additional correlated victories.
    • (D) No-cause/no-effect among rival parties.

Question-Type Tendencies & Bias Chart

  • Strengthen → more likely support author’s story.
  • Weaken / Flaw / Evaluate → biased toward alternative explanations.
  • Necessary Assumption → middle ground.
  • Inference / Most Supported → may ask to chain causal facts logically.

Inference Family & Causal Chains

  • Identify causal verbs: tends to isolate, has the effect of, in turn discourages.
  • Build the chain (e.g. \text{Media under-coverage} \rightarrow \text{Isolation of politicians} \rightarrow \text{Lower chance a resident matters} \rightarrow \text{Discouraged participation}).
  • Valid LSAT inference: Remove the cause ⇒ diminish the effect (allowed in “most supported” but not logically forced).
  • Wrong-answer patterns:
    • Normative leap (“should”, “good”, “bad”).
    • Too strong (“primary factor”, “only reason”).
    • Illicit reversal (effect → cause).

Final Strategy Checklist

  • Hear the Comparison → consciously articulate “Why?”
  • Produce alt-stories: reverse, third factor, bad study design, regression to mean.
  • For Strengthening:
    1. Covariation (match/disappearance).
    2. Mechanism.
    3. Demonstrate uniqueness/distinction.
  • For Weakening:
    1. Cause/effect mismatch.
    2. Provide rival cause or show data problems.
  • Flaw ID: locate correlation evidence + causal conclusion; anticipate “correlation ⇒ causation” description.
  • Inference questions: link causal chains; allow “remove cause → reduce effect” but NOT contrapositive reversal.

Practice: Each time you spot “more than,” “after,” or “tend to,” pause, articulate at least two alternate explanations, then predict what a covariation-style strengthen/weaken answer would look like.