Transportation analyst Maria Rodriguez and her team examined usage data from fifty bike-sharing stations across downtown Seattle. Their analysis revea...
GMAT Information and Ideas : (Ideas) Questions
Transportation analyst Maria Rodriguez and her team examined usage data from fifty bike-sharing stations across downtown Seattle. Their analysis revealed that the majority of rentals occur during weekday rush hours—a pattern that challenges the conventional wisdom among urban planning researchers. Previously, these researchers had assumed bike-sharing stations served primarily recreational cyclists and short tourist trips. Based on their findings, Rodriguez's team concludes that commuters rely on these stations as an alternative transportation method when public transit is unavailable or inconvenient.
Which finding, if true, would most directly support Rodriguez and her team's conclusion?
Weekend usage patterns showed different demographic groups using the stations.
The stations were placed in areas with high foot traffic and visibility.
Usage spikes occurred specifically during subway service disruptions and bus delays.
Other cities have reported similar bike-sharing adoption rates.
Step 1: Decode and Map the Passage
Part A: Passage Analysis Table
| Text from Passage | Analysis |
|---|---|
| Transportation analyst Maria Rodriguez and her team examined usage data from fifty bike-sharing stations across downtown Seattle. |
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| Their analysis revealed that the majority of rentals occur during weekday rush hours—a pattern that challenges the conventional wisdom among urban planning researchers. |
|
| Previously, these researchers had assumed bike-sharing stations served primarily recreational cyclists and short tourist trips. |
|
| Based on their findings, Rodriguez's team concludes that commuters rely on these stations as an alternative transportation method when public transit is unavailable or inconvenient. |
|
Part B: Passage Architecture & Core Elements
Main Point: Rodriguez's data shows bike-sharing primarily serves commuters during rush hour, not recreational users as previously assumed.
Argument Flow: The passage moves from study setup to surprising findings that contradict expert assumptions, then explains what those assumptions were, and concludes with the team's interpretation that bike-sharing serves as backup transportation for commuters.
Step 2: Interpret the Question Precisely
What's being asked? Which finding would most directly support Rodriguez's conclusion
What type of answer do we need? Evidence that would strengthen or validate their specific conclusion about commuter usage
Any limiting keywords? most directly support means we need the strongest, most relevant evidence for their conclusion
This is a Command of Evidence question asking us to identify what additional finding would best validate Rodriguez's team's conclusion that commuters use bike-sharing as an alternative when public transit is unavailable or inconvenient.
Step 3: Prethink the Answer
- Rodriguez's conclusion has two key components: (1) the users are commuters, and (2) they turn to bike-sharing specifically when public transit is unavailable or inconvenient
- The strongest supporting evidence would directly demonstrate this cause-and-effect relationship—showing that bike usage increases precisely when transit problems occur
- The right answer should show a clear connection between public transit disruptions and increased bike-sharing usage, proving that people do indeed use bikes as a backup when their usual transit fails
Weekend usage patterns showed different demographic groups using the stations.
- Weekend patterns with different demographics tells us about who uses the system on weekends
- This doesn't support the conclusion about commuters using bikes when transit is unavailable
The stations were placed in areas with high foot traffic and visibility.
- Station placement in high-traffic areas explains why stations are visible and accessible
- This doesn't demonstrate the cause-and-effect relationship between transit problems and bike usage
Usage spikes occurred specifically during subway service disruptions and bus delays.
- Shows usage spikes occur specifically during subway disruptions and bus delays
- This directly proves Rodriguez's conclusion that people turn to bikes when public transit is unavailable or inconvenient
- Demonstrates the exact cause-and-effect relationship the team proposed
Other cities have reported similar bike-sharing adoption rates.
- Similar adoption rates in other cities shows the pattern is widespread
- This doesn't support the specific conclusion about why people use the bikes (as transit alternatives)