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Difficulty: HardCorrelation vs. Causation

Match each argument on the left with the specific causal reasoning flaw it commits on the right.

  • Medical surveys reveal that individuals who use sleep-tracking applications are significantly more likely to suffer from chronic insomnia than those who do not. Clearly, the nightly use of these applications disrupts natural sleep cycles.Fails to consider that the supposed effect might actually be the cause of the phenomenon in question.
  • Data from the agricultural sector shows a strong statistical link between an increase in the sale of heavy-duty irrigation equipment and a decline in overall crop yields. Therefore, modern irrigation equipment is actually detrimental to crop health.Overlooks the possibility that both observed phenomena are independent effects of a single unstated factor.
  • An analysis of urban infrastructure indicates that over the past decade, the number of new coffee shops opened in the downtown area perfectly tracks the rise in sightings of a rare migratory bird species. Thus, the expansion of coffee culture is attracting these birds to the city.Takes for granted a causal connection between two statistically correlated events that lack any plausible mechanistic relationship.
  • Six months after the municipal government installed a new digital traffic management system, the city's overall traffic congestion decreased by 15 percent. The mayor announced that the new digital system successfully solved the city's traffic problem.Infers that one event produced a second event solely on the grounds that the first event temporally preceded the second.

Answer

The sleep tracker argument matches with reversing cause and effect. The irrigation argument matches with overlooking a common cause. The coffee shop argument matches with assuming a causal link from coincidental correlation. The traffic system argument matches with confusing temporal precedence with causality.
Each correct pairing accurately diagnoses the specific variation of the correlation-causation fallacy present in the stimulus. The sleep tracker scenario confuses the effect (insomnia) with the cause. The irrigation scenario ignores an underlying third factor (drought). The coffee shop scenario links two unrelated trends over time. The traffic scenario relies exclusively on the timeline to establish causation.

Step-by-Step Solution

1
Analyze the sleep-tracking application argument.
Identified the flaw as reversing the causal relationship.
The conclusion explicitly states that using the applications causes insomnia, whereas the premises only establish a correlation. The logical gap is the high probability that preexisting insomnia drives the use of sleep trackers.
2
Analyze the irrigation equipment argument.
Identified the flaw as ignoring a third variable.
The correlation between buying water equipment and poor crops is best explained by an external factor—like drought—which causes both the poor crops and the need for irrigation.
3
Analyze the coffee shop and bird sighting argument.
Identified the flaw as spurious correlation.
Both events (opening coffee shops, bird sightings) likely increased independently over a decade. Linking them casually without a mechanism demonstrates a fundamental misunderstanding of coincidental trends.
4
Analyze the digital traffic management argument.
Identified the flaw as a temporal sequence flaw.
The mayor's claim relies entirely on the timeline of events (installation preceding reduction), failing to rule out other possible causes for the drop in congestion.

Key Concept

Correlation vs. Causation
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Topics

Correlation vs. Causation

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