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Difficulty: EasyCorrelation vs. Causation

An analysis of urban traffic patterns has revealed that on days when city buses are running significantly behind schedule, the number of traffic accidents at major downtown intersections increases by 20 percent. Based on this analysis, the city transit authority concluded that the delayed buses are the primary cause of the increased number of traffic accidents.

Which of the following most accurately describes a flaw in the transit authority's reasoning?

  1. The argument ignores the possibility that an unstated common factor, such as adverse weather, could be responsible for both the delayed buses and the rise in accidents.Answer
  2. B
    The conclusion incorrectly equates a proportional increase in traffic accidents with a large rise in the absolute number of accidents.
  3. C
    The reasoning inappropriately infers that a phenomenon affecting specific downtown locations must characterize the entire urban area.
  4. D
    The author mistakes an event that is sufficient to cause a delay for an event that is strictly required for an accident to occur.
  5. E
    The transit authority draws a conclusion by blindly accepting the validity of the traffic data without verifying its source.

Answer

The argument ignores the possibility that an unstated common factor, such as adverse weather, could be responsible for both the delayed buses and the rise in accidents.
The correct answer accurately identifies that the argument commits a classic correlation-causation fallacy. It correctly points out that a third variable (such as adverse weather conditions) could be the true underlying cause of both correlated events, which completely undermines the transit authority's conclusion that the buses themselves are at fault.

Step-by-Step Solution

1
Analyze the structure of the argument, isolating the premises from the main conclusion.
Premise: When buses are delayed, traffic accidents increase by 20 percent. Conclusion: The delayed buses cause the increased accidents.
Separating facts from claims is necessary to identify where the logical leap occurs.
2
Evaluate the relationship between the evidence provided and the claim made.
The evidence only shows a statistical correlation (two things happening at the same time), but the conclusion insists on a direct causal relationship (one thing producing the other).
Recognizing the shift from correlation to causation exposes the vulnerability in the reasoning.
3
Identify specific manifestations of this causal flaw that would weaken the conclusion.
A common cause could exist. For instance, heavy rain or snow could independently cause buses to run late while simultaneously causing cars to crash.
Finding a plausible alternative explanation proves that the author's strict causal conclusion is unjustified.

Key Concept

Correlation vs. Causation
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Topics

Correlation vs. Causation

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